{
  "cells": [
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/TexasInstruments/edgeai-tidl-tools/blob/master/examples/jupyter_notebooks/colab/tidlrt_tools.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QyuCOiFvdRur"
      },
      "source": [
        "# Downloading the x86_64 tools required for model compilation of given target release version\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0m9iB85BtM1J",
        "outputId": "c863eded-122b-47ae-b216-f05a81af22f3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-10-02 12:51:00--  https://software-dl.ti.com/jacinto7/esd/tidl-tools/09_00_00_02/TIDL_TOOLS/TDA4VM/tidl_tools.tar.gz\n",
            "Resolving software-dl.ti.com (software-dl.ti.com)... 23.75.39.140, 2600:1406:3c00:499::b48, 2600:1406:3c00:496::b48\n",
            "Connecting to software-dl.ti.com (software-dl.ti.com)|23.75.39.140|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Moved Temporarily\n",
            "Location: https://www.ti.com/general/docs/licreg/anonymousproddownload.tsp?downloadPage=true&location=https://software-dl.ti.com/jacinto7/esd/tidl-tools/09_00_00_02/TIDL_TOOLS/TDA4VM/tidl_tools.tar.gz [following]\n",
            "--2023-10-02 12:51:00--  https://www.ti.com/general/docs/licreg/anonymousproddownload.tsp?downloadPage=true&location=https://software-dl.ti.com/jacinto7/esd/tidl-tools/09_00_00_02/TIDL_TOOLS/TDA4VM/tidl_tools.tar.gz\n",
            "Resolving www.ti.com (www.ti.com)... 23.75.39.140, 2600:1406:3c00:188::b48, 2600:1406:3c00:186::b48\n",
            "Connecting to www.ti.com (www.ti.com)|23.75.39.140|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Moved Temporarily\n",
            "Location: https://software-dl.ti.com/jacinto7/esd/tidl-tools/09_00_00_02/TIDL_TOOLS/TDA4VM/tidl_tools.tar.gz?tracked=1 [following]\n",
            "--2023-10-02 12:51:01--  https://software-dl.ti.com/jacinto7/esd/tidl-tools/09_00_00_02/TIDL_TOOLS/TDA4VM/tidl_tools.tar.gz?tracked=1\n",
            "Connecting to software-dl.ti.com (software-dl.ti.com)|23.75.39.140|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Moved Temporarily\n",
            "Location: https://downloads.ti.com/jacinto7/esd/tidl-tools/09_00_00_02/TIDL_TOOLS/TDA4VM/tidl_tools.tar.gz?tracked=1 [following]\n",
            "--2023-10-02 12:51:01--  https://downloads.ti.com/jacinto7/esd/tidl-tools/09_00_00_02/TIDL_TOOLS/TDA4VM/tidl_tools.tar.gz?tracked=1\n",
            "Resolving downloads.ti.com (downloads.ti.com)... 23.55.199.190\n",
            "Connecting to downloads.ti.com (downloads.ti.com)|23.55.199.190|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 23785924 (23M) [application/x-gzip]\n",
            "Saving to: ‘tidl_tools.tar.gz’\n",
            "\n",
            "tidl_tools.tar.gz   100%[===================>]  22.68M  92.0MB/s    in 0.2s    \n",
            "\n",
            "2023-10-02 12:51:01 (92.0 MB/s) - ‘tidl_tools.tar.gz’ saved [23785924/23785924]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "!wget https://software-dl.ti.com/jacinto7/esd/tidl-tools/09_00_00_02/TIDL_TOOLS/TDA4VM/tidl_tools.tar.gz\n",
        "!tar -xzf tidl_tools.tar.gz\n",
        "!rm tidl_tools.tar.gz"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7q1USm_hdoqp"
      },
      "source": [
        "# Downloading a sample model (renet18.onnx) and an image for testing"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QlA5XCkfxPjE",
        "outputId": "35d1eb63-49ce-4ce6-e1eb-ebf015ed3f62"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-10-02 12:51:05--  https://akm-img-a-in.tosshub.com/indiatoday/images/story/201804/jet.jpeg\n",
            "Resolving akm-img-a-in.tosshub.com (akm-img-a-in.tosshub.com)... 23.217.118.47, 23.217.118.65, 2600:1406:3c::6863:ee2a, ...\n",
            "Connecting to akm-img-a-in.tosshub.com (akm-img-a-in.tosshub.com)|23.217.118.47|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 30622 (30K) [image/jpeg]\n",
            "Saving to: ‘jet.jpeg’\n",
            "\n",
            "\rjet.jpeg              0%[                    ]       0  --.-KB/s               \rjet.jpeg            100%[===================>]  29.90K  --.-KB/s    in 0s      \n",
            "\n",
            "2023-10-02 12:51:05 (330 MB/s) - ‘jet.jpeg’ saved [30622/30622]\n",
            "\n",
            "--2023-10-02 12:51:05--  https://git.ti.com/cgit/jacinto-ai/jacinto-ai-modelzoo/plain/models/vision/classification/imagenet1k/torchvision/resnet18_opset9.onnx\n",
            "Resolving git.ti.com (git.ti.com)... 198.47.28.207\n",
            "Connecting to git.ti.com (git.ti.com)|198.47.28.207|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 46808064 (45M) [application/octet-stream]\n",
            "Saving to: ‘resnet18_opset9.onnx’\n",
            "\n",
            "resnet18_opset9.onn 100%[===================>]  44.64M  52.5MB/s    in 0.8s    \n",
            "\n",
            "2023-10-02 12:51:06 (52.5 MB/s) - ‘resnet18_opset9.onnx’ saved [46808064/46808064]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "!wget https://akm-img-a-in.tosshub.com/indiatoday/images/story/201804/jet.jpeg\n",
        "!wget https://git.ti.com/cgit/jacinto-ai/jacinto-ai-modelzoo/plain/models/vision/classification/imagenet1k/torchvision/resnet18_opset9.onnx\n",
        "!mkdir /content/resnet18/\n",
        "!mv jet.jpeg /content/resnet18/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 380
        },
        "id": "_xmguPnzjPFQ",
        "outputId": "8dbcbe52-118a-4b14-94b6-73cea80bb9f5"
      },
      "outputs": [
        {
          "data": {
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",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import glob\n",
        "from IPython.display import Image, display\n",
        "for imageName in glob.glob('/content/resnet18/*.jpeg'):\n",
        "    display(Image(filename=imageName))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mHiABfuWd_Pu"
      },
      "source": [
        "# Preparing configuration text files and list of inputs for quantization/calibration"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "rfWwYzBrPDHI"
      },
      "outputs": [],
      "source": [
        "!echo \"perfSimConfig = /content/tidl_tools/device_config.cfg\" >> /content/resnet18/config\n",
        "!echo \"/content/resnet18/jet.jpeg 895\" >> /content/resnet18/in_data_list.txt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x23cFOiYeRFu"
      },
      "source": [
        "# Model import/compilation to generate artifacts for model inference on device"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fgDkbie4IKt8",
        "outputId": "7de1fc75-867e-42f7-f7c4-7efff303f594"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "ONNX Model (Proto) File  : /content/resnet18_opset9.onnx  \n",
            "TIDL Network File      : /content/resnet18/tidl_net.bin  \n",
            "TIDL IO Info File      : /content/resnet18/tidl_io_buff  \n",
            "Current ONNX OpSet Version   : 9  \n",
            "Empty prototxt path, running calibration\n",
            "\n",
            "~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~\n",
            "\n",
            "Processing config file #0 : /content/resnet18/config.qunat_stats_config.txt \n",
            " Freeing memory for user provided Net\n",
            " ----------------------- TIDL Process with REF_ONLY FLOW ------------------------\n",
            "\n",
            "#    0 . .. T    8317.90  .... ..... ... .... .....\n",
            " \n",
            " \n",
            " *****************   Calibration iteration number 0 started ************************ \n",
            " \n",
            " \n",
            " \n",
            "\n",
            "~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~\n",
            "\n",
            "Processing config file #0 : /content/resnet18/config.qunat_stats_config.txt \n",
            " Freeing memory for user provided Net\n",
            " ----------------------- TIDL Process with REF_ONLY FLOW ------------------------\n",
            "\n",
            "#    0 . .. T    6048.46  .... ..... ... .... .....\n",
            " \n",
            " \n",
            " *****************   Calibration iteration number 0 completed ************************ \n",
            " \n",
            " \n",
            " \n",
            "\n",
            "------------------ Network Compiler Traces -----------------------------\n",
            "successful Memory allocation\n",
            "****************************************************\n",
            "**                ALL MODEL CHECK PASSED          **\n",
            "****************************************************\n",
            "\n"
          ]
        }
      ],
      "source": [
        "!/content/tidl_tools/tidl_model_import.out /content/resnet18/config --modelType 2 \\\n",
        "--inputNetFile /content/resnet18_opset9.onnx --outputNetFile /content/resnet18/tidl_net.bin \\\n",
        "--outputParamsFile /content/resnet18/tidl_io_buff  --inDataNorm 1 \\\n",
        "--inMean 123.675 116.28 103.53  --inScale 0.017125 0.017507 0.017429 \\\n",
        "--inData /content/resnet18/in_data_list.txt --inFileFormat 2 \\\n",
        "--tidlStatsTool /content/tidl_tools/PC_dsp_test_dl_algo.out \\\n",
        "--perfSimTool /content/tidl_tools/ti_cnnperfsim.out \\\n",
        "--graphVizTool /content/tidl_tools/tidl_graphVisualiser.out \\\n",
        "--inHeight 224 --inWidth 224 --inNumChannels 3 --numFrames 1\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k68JUBfoexkk"
      },
      "source": [
        "# Running inference of the imported model artefacts using PC Host emulation mode.\n",
        "Here last number is index of the  detected object in the ImageNet [categories/labels](https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a) for the given input image\n",
        "\n",
        "895: 'warplane, military plane\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gBW3Lz4lRwJp",
        "outputId": "a355f0ce-8b4e-4b26-8799-49fd1db03d7e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Processing config file #0 : /content/resnet18/config \n",
            " Freeing memory for user provided Net\n",
            " ----------------------- TIDL Process with REF_ONLY FLOW ------------------------\n",
            "\n",
            "#    0 . .. T    1645.87  .... ..... ...\n",
            " A :   895, 1.0000, 1.0000,   895 .... ....."
          ]
        }
      ],
      "source": [
        "!/content/tidl_tools/PC_dsp_test_dl_algo.out s:/content/resnet18/config \\\n",
        "--netBinFile /content/resnet18/tidl_net.bin \\\n",
        "--ioConfigFile /content/resnet18/tidl_io_buff1.bin \\\n",
        "--inData /content/resnet18/in_data_list.txt --inFileFormat 2 \\\n",
        "--outData /content/resnet18/jet_tidl_out.bin --postProcType 1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_p11ZhI8gPah"
      },
      "source": [
        "# The generated model artefacts, in this case \"resnet18\" directory can be copied to EVM board file-system (/opt/ directory) to run the inference on the device using below commands\n",
        "\n",
        "\n",
        "```\n",
        "root@ j7-evm:~# cd /opt/vision_apps\n",
        "root@ j7-evm:~# source ./vision_apps_init.sh\n",
        "root@ j7-evm:~# cd /opt/tidl_test\n",
        "root@ j7-evm:/opt/tidl_test# export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib\n",
        "root@ j7-evm:~# echo \"/opt/resnet18/jet.jpeg 895\" > /opt/resnet18/in_data_list.txt\n",
        "root@ j7-evm:/opt/tidl_test# ./TI_DEVICE_a72_test_dl_algo_host_rt.out s:/opt/resnet18/config \\\n",
        "--netBinFile /opt/resnet18/tidl_net.bin \\\n",
        "--ioConfigFile /opt/resnet18/tidl_io_buff1.bin \\\n",
        "--inData /opt/resnet18/in_data_list.txt --inFileFormat 2 \\\n",
        "--outData /opt/resnet18/jet_tidl_out.bin --postProcType 1\n",
        "```\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ArqtansViSTb"
      },
      "source": [
        "# SVG file in the artefacts folder can be used to visualize the import model structure with more details"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "4gFiuecTXegz",
        "outputId": "72ad96f1-df3c-4caa-e7e2-0595b8775f4e"
      },
      "outputs": [
        {
          "data": {
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  Inputs:\n      [0] \n   Outputs:\n      [1] numDim=0 dims=[1,64,112,112]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[831488,12992,113]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n         tensorScale=36.255119\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M144.17,-1281C144.17,-1281 66.83,-1281 66.83,-1281 63.67,-1281 60.5,-1277.83 60.5,-1274.67 60.5,-1274.67 60.5,-1268.33 60.5,-1268.33 60.5,-1265.17 63.67,-1262 66.83,-1262 66.83,-1262 144.17,-1262 144.17,-1262 147.33,-1262 150.5,-1265.17 150.5,-1268.33 150.5,-1268.33 150.5,-1274.67 150.5,-1274.67 150.5,-1277.83 147.33,-1281 144.17,-1281\"/>\n<text text-anchor=\"middle\" x=\"105.5\" y=\"-1269\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [1 1]</text>\n</g>\n<!-- Layer 0: TIDL_DataLayer &quot;input.1_original&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 dataQ=0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[0] numDim=0 dims=[1,3,224,224] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[3,3] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[156639,52213,227]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=0\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,255.000000)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=1.000000\n&#45;&gt;Layer 1: TIDL_ConvolutionLayer &quot;125&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=3 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[7,7] strideH/W=[2,2] padH/W=[3,3] dilationH/W=[1,1]\n &#160;&#160;weightScale=18562.621094 biasScale=94.183266\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[0] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[1] numDim=0 dims=[1,64,112,112] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[831488,12992,113]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=36.255119\n -->\n<g id=\"edge1\" class=\"edge\">\n<title>Layer 0: TIDL_DataLayer &quot;input.1_original&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 dataQ=0\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Outputs:\n      [0] numDim=0 dims=[1,3,224,224]  elementType=TIDL_UnsignedChar\n         padH/W=[3,3] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[156639,52213,227]\n         dataQ=0 roundBits=0\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,255.000000)\n         tensorScale=1.000000\n-&gt;Layer 1: TIDL_ConvolutionLayer &quot;125&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=3 numOutChannels=64 numGroups=1\n   kernelH/W=[7,7] strideH/W=[2,2] padH/W=[3,3] dilationH/W=[1,1]\n   weightScale=18562.621094 biasScale=94.183266\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [0] \n   Outputs:\n      [1] numDim=0 dims=[1,64,112,112]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[831488,12992,113]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n         tensorScale=36.255119\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M105.5,-1305.59C105.5,-1299.95 105.5,-1292.54 105.5,-1286.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"105.5,-1281.11 107.75,-1286.11 105.5,-1283.61 105.5,-1286.11 105.5,-1286.11 105.5,-1286.11 105.5,-1283.61 103.25,-1286.11 105.5,-1281.11 105.5,-1281.11\"/>\n<text text-anchor=\"middle\" x=\"127.5\" y=\"-1291.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x3x224x224</text>\n</g>\n<!-- Layer 2: TIDL_PoolingLayer &quot;126&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;poolingtype=TIDL_MaxPooling numChannels=64\n &#160;&#160;inDataQ=0 outDataQ=0 useCeil=0\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1]\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[1] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[2] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=0\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=36.255119\n -->\n<g id=\"node3\" class=\"node\">\n<title>Layer 2: TIDL_PoolingLayer &quot;126&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   poolingtype=TIDL_MaxPooling numChannels=64\n   inDataQ=0 outDataQ=0 useCeil=0\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1]\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [1] \n   Outputs:\n      [2] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=0\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n         tensorScale=36.255119\n</title>\n<path fill=\"#338533\" stroke=\"#000000\" d=\"M134.17,-1237C134.17,-1237 76.83,-1237 76.83,-1237 73.67,-1237 70.5,-1233.83 70.5,-1230.67 70.5,-1230.67 70.5,-1224.33 70.5,-1224.33 70.5,-1221.17 73.67,-1218 76.83,-1218 76.83,-1218 134.17,-1218 134.17,-1218 137.33,-1218 140.5,-1221.17 140.5,-1224.33 140.5,-1224.33 140.5,-1230.67 140.5,-1230.67 140.5,-1233.83 137.33,-1237 134.17,-1237\"/>\n<text text-anchor=\"middle\" x=\"105.5\" y=\"-1225\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Pooling [2 2]</text>\n</g>\n<!-- Layer 1: TIDL_ConvolutionLayer &quot;125&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=3 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[7,7] strideH/W=[2,2] padH/W=[3,3] dilationH/W=[1,1]\n &#160;&#160;weightScale=18562.621094 biasScale=94.183266\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[0] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[1] numDim=0 dims=[1,64,112,112] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[831488,12992,113]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=36.255119\n&#45;&gt;Layer 2: TIDL_PoolingLayer &quot;126&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;poolingtype=TIDL_MaxPooling numChannels=64\n &#160;&#160;inDataQ=0 outDataQ=0 useCeil=0\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1]\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[1] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[2] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=0\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=36.255119\n -->\n<g id=\"edge2\" class=\"edge\">\n<title>Layer 1: TIDL_ConvolutionLayer &quot;125&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=3 numOutChannels=64 numGroups=1\n   kernelH/W=[7,7] strideH/W=[2,2] padH/W=[3,3] dilationH/W=[1,1]\n   weightScale=18562.621094 biasScale=94.183266\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [0] \n   Outputs:\n      [1] numDim=0 dims=[1,64,112,112]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[831488,12992,113]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n         tensorScale=36.255119\n-&gt;Layer 2: TIDL_PoolingLayer &quot;126&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   poolingtype=TIDL_MaxPooling numChannels=64\n   inDataQ=0 outDataQ=0 useCeil=0\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1]\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [1] \n   Outputs:\n      [2] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=0\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n         tensorScale=36.255119\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M105.5,-1261.59C105.5,-1255.95 105.5,-1248.54 105.5,-1242.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"105.5,-1237.11 107.75,-1242.11 105.5,-1239.61 105.5,-1242.11 105.5,-1242.11 105.5,-1242.11 105.5,-1239.61 103.25,-1242.11 105.5,-1237.11 105.5,-1237.11\"/>\n<text text-anchor=\"middle\" x=\"129.5\" y=\"-1247.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x112x112</text>\n</g>\n<!-- Layer 3: TIDL_ConvolutionLayer &quot;129&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=341.785248 biasScale=116.130249\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[2] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[3] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=7\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.766377)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=96.808319\n -->\n<g id=\"node4\" class=\"node\">\n<title>Layer 3: TIDL_ConvolutionLayer &quot;129&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=341.785248 biasScale=116.130249\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [2] \n   Outputs:\n      [3] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=7\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.766377)\n         tensorScale=96.808319\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M108.17,-1193C108.17,-1193 30.83,-1193 30.83,-1193 27.67,-1193 24.5,-1189.83 24.5,-1186.67 24.5,-1186.67 24.5,-1180.33 24.5,-1180.33 24.5,-1177.17 27.67,-1174 30.83,-1174 30.83,-1174 108.17,-1174 108.17,-1174 111.33,-1174 114.5,-1177.17 114.5,-1180.33 114.5,-1180.33 114.5,-1186.67 114.5,-1186.67 114.5,-1189.83 111.33,-1193 108.17,-1193\"/>\n<text text-anchor=\"middle\" x=\"69.5\" y=\"-1181\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [3 3]</text>\n</g>\n<!-- Layer 2: TIDL_PoolingLayer &quot;126&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;poolingtype=TIDL_MaxPooling numChannels=64\n &#160;&#160;inDataQ=0 outDataQ=0 useCeil=0\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1]\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[1] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[2] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=0\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=36.255119\n&#45;&gt;Layer 3: TIDL_ConvolutionLayer &quot;129&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=341.785248 biasScale=116.130249\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[2] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[3] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=7\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.766377)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=96.808319\n -->\n<g id=\"edge3\" class=\"edge\">\n<title>Layer 2: TIDL_PoolingLayer &quot;126&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   poolingtype=TIDL_MaxPooling numChannels=64\n   inDataQ=0 outDataQ=0 useCeil=0\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1]\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [1] \n   Outputs:\n      [2] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=0\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n         tensorScale=36.255119\n-&gt;Layer 3: TIDL_ConvolutionLayer &quot;129&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=341.785248 biasScale=116.130249\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [2] \n   Outputs:\n      [3] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=7\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.766377)\n         tensorScale=96.808319\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M95.88,-1217.68C93.39,-1215.27 90.78,-1212.6 88.5,-1210 85.08,-1206.1 81.61,-1201.63 78.58,-1197.52\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"75.5,-1193.27 80.26,-1196 76.97,-1195.29 78.43,-1197.32 78.43,-1197.32 78.43,-1197.32 76.97,-1195.29 76.61,-1198.64 75.5,-1193.27 75.5,-1193.27\"/>\n<text text-anchor=\"middle\" x=\"108.5\" y=\"-1203.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[4] [2] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[5] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=31.399418\n -->\n<g id=\"node6\" class=\"node\">\n<title>Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [4] [2] \n   Outputs:\n      [5] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n         tensorScale=31.399418\n</title>\n<path fill=\"#209070\" stroke=\"#000000\" d=\"M134.17,-1105C134.17,-1105 76.83,-1105 76.83,-1105 73.67,-1105 70.5,-1101.83 70.5,-1098.67 70.5,-1098.67 70.5,-1092.33 70.5,-1092.33 70.5,-1089.17 73.67,-1086 76.83,-1086 76.83,-1086 134.17,-1086 134.17,-1086 137.33,-1086 140.5,-1089.17 140.5,-1092.33 140.5,-1092.33 140.5,-1098.67 140.5,-1098.67 140.5,-1101.83 137.33,-1105 134.17,-1105\"/>\n<text text-anchor=\"middle\" x=\"105.5\" y=\"-1093\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">EltWise [5 5]</text>\n</g>\n<!-- Layer 2: TIDL_PoolingLayer &quot;126&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;poolingtype=TIDL_MaxPooling numChannels=64\n &#160;&#160;inDataQ=0 outDataQ=0 useCeil=0\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1]\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[1] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[2] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=0\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=36.255119\n&#45;&gt;Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[4] [2] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[5] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=31.399418\n -->\n<g id=\"edge6\" class=\"edge\">\n<title>Layer 2: TIDL_PoolingLayer &quot;126&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   poolingtype=TIDL_MaxPooling numChannels=64\n   inDataQ=0 outDataQ=0 useCeil=0\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1]\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [1] \n   Outputs:\n      [2] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=0\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.137347)\n         tensorScale=36.255119\n-&gt;Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [4] [2] \n   Outputs:\n      [5] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n         tensorScale=31.399418\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M122.02,-1217.68C124.64,-1215.53 126.97,-1212.97 128.5,-1210 148.19,-1171.65 148.19,-1151.35 128.5,-1113 127.74,-1111.51 126.77,-1110.13 125.67,-1108.85\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"122.02,-1105.32 127.18,-1107.18 123.82,-1107.06 125.61,-1108.8 125.61,-1108.8 125.61,-1108.8 123.82,-1107.06 124.05,-1110.41 122.02,-1105.32 122.02,-1105.32\"/>\n<text text-anchor=\"middle\" x=\"163.5\" y=\"-1159.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 4: TIDL_ConvolutionLayer &quot;131&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=166.065292 biasScale=71.695251\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[3] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[4] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;3.471402,3.248468)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=31.399418\n -->\n<g id=\"node5\" class=\"node\">\n<title>Layer 4: TIDL_ConvolutionLayer &quot;131&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=166.065292 biasScale=71.695251\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [3] \n   Outputs:\n      [4] numDim=0 dims=[1,64,56,56]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-3.471402,3.248468)\n         tensorScale=31.399418\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M108.17,-1149C108.17,-1149 30.83,-1149 30.83,-1149 27.67,-1149 24.5,-1145.83 24.5,-1142.67 24.5,-1142.67 24.5,-1136.33 24.5,-1136.33 24.5,-1133.17 27.67,-1130 30.83,-1130 30.83,-1130 108.17,-1130 108.17,-1130 111.33,-1130 114.5,-1133.17 114.5,-1136.33 114.5,-1136.33 114.5,-1142.67 114.5,-1142.67 114.5,-1145.83 111.33,-1149 108.17,-1149\"/>\n<text text-anchor=\"middle\" x=\"69.5\" y=\"-1137\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [4 4]</text>\n</g>\n<!-- Layer 3: TIDL_ConvolutionLayer &quot;129&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=341.785248 biasScale=116.130249\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[2] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[3] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=7\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.766377)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=96.808319\n&#45;&gt;Layer 4: TIDL_ConvolutionLayer &quot;131&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=166.065292 biasScale=71.695251\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[3] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[4] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;3.471402,3.248468)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=31.399418\n -->\n<g id=\"edge4\" class=\"edge\">\n<title>Layer 3: TIDL_ConvolutionLayer &quot;129&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=341.785248 biasScale=116.130249\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [2] \n   Outputs:\n      [3] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=7\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.766377)\n         tensorScale=96.808319\n-&gt;Layer 4: TIDL_ConvolutionLayer &quot;131&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=166.065292 biasScale=71.695251\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [3] \n   Outputs:\n      [4] numDim=0 dims=[1,64,56,56]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-3.471402,3.248468)\n         tensorScale=31.399418\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M69.5,-1173.59C69.5,-1167.95 69.5,-1160.54 69.5,-1154.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"69.5,-1149.11 71.75,-1154.11 69.5,-1151.61 69.5,-1154.11 69.5,-1154.11 69.5,-1154.11 69.5,-1151.61 67.25,-1154.11 69.5,-1149.11 69.5,-1149.11\"/>\n<text text-anchor=\"middle\" x=\"89.5\" y=\"-1159.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 4: TIDL_ConvolutionLayer &quot;131&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=166.065292 biasScale=71.695251\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[3] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[4] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;3.471402,3.248468)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=31.399418\n&#45;&gt;Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[4] [2] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[5] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=31.399418\n -->\n<g id=\"edge5\" class=\"edge\">\n<title>Layer 4: TIDL_ConvolutionLayer &quot;131&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=166.065292 biasScale=71.695251\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [3] \n   Outputs:\n      [4] numDim=0 dims=[1,64,56,56]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-3.471402,3.248468)\n         tensorScale=31.399418\n-&gt;Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [4] [2] \n   Outputs:\n      [5] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n         tensorScale=31.399418\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M75.5,-1129.73C79.09,-1124.69 83.84,-1118.31 88.5,-1113 89.64,-1111.7 90.86,-1110.39 92.11,-1109.09\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"95.88,-1105.32 93.94,-1110.45 94.11,-1107.09 92.34,-1108.86 92.34,-1108.86 92.34,-1108.86 94.11,-1107.09 90.75,-1107.27 95.88,-1105.32 95.88,-1105.32\"/>\n<text text-anchor=\"middle\" x=\"108.5\" y=\"-1115.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 6: TIDL_ConvolutionLayer &quot;136&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=457.212402 biasScale=105.967316\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[5] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[6] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.763962)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=56.078918\n -->\n<g id=\"node7\" class=\"node\">\n<title>Layer 6: TIDL_ConvolutionLayer &quot;136&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=457.212402 biasScale=105.967316\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [5] \n   Outputs:\n      [6] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.763962)\n         tensorScale=56.078918\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M99.17,-1061C99.17,-1061 21.83,-1061 21.83,-1061 18.67,-1061 15.5,-1057.83 15.5,-1054.67 15.5,-1054.67 15.5,-1048.33 15.5,-1048.33 15.5,-1045.17 18.67,-1042 21.83,-1042 21.83,-1042 99.17,-1042 99.17,-1042 102.33,-1042 105.5,-1045.17 105.5,-1048.33 105.5,-1048.33 105.5,-1054.67 105.5,-1054.67 105.5,-1057.83 102.33,-1061 99.17,-1061\"/>\n<text text-anchor=\"middle\" x=\"60.5\" y=\"-1049\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [6 6]</text>\n</g>\n<!-- Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[4] [2] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[5] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=31.399418\n&#45;&gt;Layer 6: TIDL_ConvolutionLayer &quot;136&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=457.212402 biasScale=105.967316\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[5] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[6] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.763962)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=56.078918\n -->\n<g id=\"edge7\" class=\"edge\">\n<title>Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [4] [2] \n   Outputs:\n      [5] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n         tensorScale=31.399418\n-&gt;Layer 6: TIDL_ConvolutionLayer &quot;136&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=457.212402 biasScale=105.967316\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [5] \n   Outputs:\n      [6] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.763962)\n         tensorScale=56.078918\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M89.98,-1085.95C86.35,-1083.61 82.64,-1080.91 79.5,-1078 75.49,-1074.28 71.74,-1069.63 68.65,-1065.31\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"65.79,-1061.16 70.48,-1064.01 67.21,-1063.22 68.63,-1065.28 68.63,-1065.28 68.63,-1065.28 67.21,-1063.22 66.78,-1066.56 65.79,-1061.16 65.79,-1061.16\"/>\n<text text-anchor=\"middle\" x=\"99.5\" y=\"-1071.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[7] [5] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[8] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=26.770767\n -->\n<g id=\"node9\" class=\"node\">\n<title>Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [7] [5] \n   Outputs:\n      [8] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n         tensorScale=26.770767\n</title>\n<path fill=\"#209070\" stroke=\"#000000\" d=\"M130.17,-973C130.17,-973 72.83,-973 72.83,-973 69.67,-973 66.5,-969.83 66.5,-966.67 66.5,-966.67 66.5,-960.33 66.5,-960.33 66.5,-957.17 69.67,-954 72.83,-954 72.83,-954 130.17,-954 130.17,-954 133.33,-954 136.5,-957.17 136.5,-960.33 136.5,-960.33 136.5,-966.67 136.5,-966.67 136.5,-969.83 133.33,-973 130.17,-973\"/>\n<text text-anchor=\"middle\" x=\"101.5\" y=\"-961\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">EltWise [8 8]</text>\n</g>\n<!-- Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[4] [2] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[5] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=31.399418\n&#45;&gt;Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[7] [5] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[8] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=26.770767\n -->\n<g id=\"edge10\" class=\"edge\">\n<title>Layer 5: TIDL_EltWiseLayer &quot;133&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [4] [2] \n   Outputs:\n      [5] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.554224)\n         tensorScale=31.399418\n-&gt;Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [7] [5] \n   Outputs:\n      [8] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n         tensorScale=26.770767\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M114.78,-1085.83C116.71,-1083.49 118.46,-1080.82 119.5,-1078 134.36,-1037.53 136.86,-1020.46 119.5,-981 118.89,-979.62 118.1,-978.3 117.2,-977.06\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"113.76,-973.13 118.74,-975.41 115.41,-975.01 117.05,-976.89 117.05,-976.89 117.05,-976.89 115.41,-975.01 115.36,-978.37 113.76,-973.13 113.76,-973.13\"/>\n<text text-anchor=\"middle\" x=\"152.5\" y=\"-1027.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 7: TIDL_ConvolutionLayer &quot;138&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=122.208427 biasScale=109.348160\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[6] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[7] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;5.229585,3.063043)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=13.385384\n -->\n<g id=\"node8\" class=\"node\">\n<title>Layer 7: TIDL_ConvolutionLayer &quot;138&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=122.208427 biasScale=109.348160\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [6] \n   Outputs:\n      [7] numDim=0 dims=[1,64,56,56]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-5.229585,3.063043)\n         tensorScale=13.385384\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M99.17,-1017C99.17,-1017 21.83,-1017 21.83,-1017 18.67,-1017 15.5,-1013.83 15.5,-1010.67 15.5,-1010.67 15.5,-1004.33 15.5,-1004.33 15.5,-1001.17 18.67,-998 21.83,-998 21.83,-998 99.17,-998 99.17,-998 102.33,-998 105.5,-1001.17 105.5,-1004.33 105.5,-1004.33 105.5,-1010.67 105.5,-1010.67 105.5,-1013.83 102.33,-1017 99.17,-1017\"/>\n<text text-anchor=\"middle\" x=\"60.5\" y=\"-1005\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [7 7]</text>\n</g>\n<!-- Layer 6: TIDL_ConvolutionLayer &quot;136&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=457.212402 biasScale=105.967316\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[5] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[6] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.763962)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=56.078918\n&#45;&gt;Layer 7: TIDL_ConvolutionLayer &quot;138&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=122.208427 biasScale=109.348160\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[6] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[7] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;5.229585,3.063043)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=13.385384\n -->\n<g id=\"edge8\" class=\"edge\">\n<title>Layer 6: TIDL_ConvolutionLayer &quot;136&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=457.212402 biasScale=105.967316\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [5] \n   Outputs:\n      [6] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.763962)\n         tensorScale=56.078918\n-&gt;Layer 7: TIDL_ConvolutionLayer &quot;138&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=122.208427 biasScale=109.348160\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [6] \n   Outputs:\n      [7] numDim=0 dims=[1,64,56,56]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-5.229585,3.063043)\n         tensorScale=13.385384\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M60.5,-1041.59C60.5,-1035.95 60.5,-1028.54 60.5,-1022.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"60.5,-1017.11 62.75,-1022.11 60.5,-1019.61 60.5,-1022.11 60.5,-1022.11 60.5,-1022.11 60.5,-1019.61 58.25,-1022.11 60.5,-1017.11 60.5,-1017.11\"/>\n<text text-anchor=\"middle\" x=\"80.5\" y=\"-1027.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 7: TIDL_ConvolutionLayer &quot;138&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=122.208427 biasScale=109.348160\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[6] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[7] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;5.229585,3.063043)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=13.385384\n&#45;&gt;Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[7] [5] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[8] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=26.770767\n -->\n<g id=\"edge9\" class=\"edge\">\n<title>Layer 7: TIDL_ConvolutionLayer &quot;138&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=64 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=122.208427 biasScale=109.348160\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [6] \n   Outputs:\n      [7] numDim=0 dims=[1,64,56,56]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-5.229585,3.063043)\n         tensorScale=13.385384\n-&gt;Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [7] [5] \n   Outputs:\n      [8] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n         tensorScale=26.770767\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M65.93,-997.98C69.46,-992.78 74.36,-986.16 79.5,-981 81.02,-979.48 82.68,-977.98 84.39,-976.55\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"88.43,-973.34 85.92,-978.21 86.47,-974.89 84.51,-976.45 84.51,-976.45 84.51,-976.45 86.47,-974.89 83.11,-974.69 88.43,-973.34 88.43,-973.34\"/>\n<text text-anchor=\"middle\" x=\"99.5\" y=\"-983.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 9: TIDL_ConvolutionLayer &quot;143&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=601.798462 biasScale=172.955078\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[8] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[9] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.288182)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=62.932056\n -->\n<g id=\"node10\" class=\"node\">\n<title>Layer 9: TIDL_ConvolutionLayer &quot;143&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=601.798462 biasScale=172.955078\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [8] \n   Outputs:\n      [9] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.288182)\n         tensorScale=62.932056\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M101.17,-929C101.17,-929 23.83,-929 23.83,-929 20.67,-929 17.5,-925.83 17.5,-922.67 17.5,-922.67 17.5,-916.33 17.5,-916.33 17.5,-913.17 20.67,-910 23.83,-910 23.83,-910 101.17,-910 101.17,-910 104.33,-910 107.5,-913.17 107.5,-916.33 107.5,-916.33 107.5,-922.67 107.5,-922.67 107.5,-925.83 104.33,-929 101.17,-929\"/>\n<text text-anchor=\"middle\" x=\"62.5\" y=\"-917\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [9 9]</text>\n</g>\n<!-- Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[7] [5] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[8] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=26.770767\n&#45;&gt;Layer 9: TIDL_ConvolutionLayer &quot;143&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=601.798462 biasScale=172.955078\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[8] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[9] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.288182)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=62.932056\n -->\n<g id=\"edge11\" class=\"edge\">\n<title>Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [7] [5] \n   Outputs:\n      [8] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n         tensorScale=26.770767\n-&gt;Layer 9: TIDL_ConvolutionLayer &quot;143&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=601.798462 biasScale=172.955078\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [8] \n   Outputs:\n      [9] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.288182)\n         tensorScale=62.932056\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M88.32,-953.76C85.26,-951.43 82.12,-948.77 79.5,-946 75.96,-942.25 72.66,-937.69 69.93,-933.46\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"67.2,-929.06 71.75,-932.13 68.52,-931.19 69.84,-933.31 69.84,-933.31 69.84,-933.31 68.52,-931.19 67.92,-934.5 67.2,-929.06 67.2,-929.06\"/>\n<text text-anchor=\"middle\" x=\"99.5\" y=\"-939.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 10: TIDL_ConvolutionLayer &quot;147&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n &#160;&#160;weightScale=184.904083 biasScale=115.278854\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[8] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[10] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=7\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.042818,1.654941)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=38.672062\n -->\n<g id=\"node12\" class=\"node\">\n<title>Layer 10: TIDL_ConvolutionLayer &quot;147&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n   kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n   weightScale=184.904083 biasScale=115.278854\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [8] \n   Outputs:\n      [10] numDim=0 dims=[1,128,28,28]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=7\n         min/maxValue=(0,0) min/maxTensorValue=(-2.042818,1.654941)\n         tensorScale=38.672062\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M192.17,-902C192.17,-902 104.83,-902 104.83,-902 101.67,-902 98.5,-898.83 98.5,-895.67 98.5,-895.67 98.5,-889.33 98.5,-889.33 98.5,-886.17 101.67,-883 104.83,-883 104.83,-883 192.17,-883 192.17,-883 195.33,-883 198.5,-886.17 198.5,-889.33 198.5,-889.33 198.5,-895.67 198.5,-895.67 198.5,-898.83 195.33,-902 192.17,-902\"/>\n<text text-anchor=\"middle\" x=\"148.5\" y=\"-890\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [11 10]</text>\n</g>\n<!-- Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[7] [5] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[8] numDim=0 dims=[1,64,56,56] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=26.770767\n&#45;&gt;Layer 10: TIDL_ConvolutionLayer &quot;147&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n &#160;&#160;weightScale=184.904083 biasScale=115.278854\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[8] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[10] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=7\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.042818,1.654941)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=38.672062\n -->\n<g id=\"edge13\" class=\"edge\">\n<title>Layer 8: TIDL_EltWiseLayer &quot;140&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [7] [5] \n   Outputs:\n      [8] numDim=0 dims=[1,64,56,56]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[217088,3392,57]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.117522)\n         tensorScale=26.770767\n-&gt;Layer 10: TIDL_ConvolutionLayer &quot;147&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n   kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n   weightScale=184.904083 biasScale=115.278854\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [8] \n   Outputs:\n      [10] numDim=0 dims=[1,128,28,28]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=7\n         min/maxValue=(0,0) min/maxTensorValue=(-2.042818,1.654941)\n         tensorScale=38.672062\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M111.98,-953.95C114.6,-951.54 117.3,-948.8 119.5,-946 129.11,-933.8 137.36,-917.99 142.58,-906.92\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"144.76,-902.2 144.71,-907.68 143.71,-904.47 142.67,-906.74 142.67,-906.74 142.67,-906.74 143.71,-904.47 140.62,-905.8 144.76,-902.2 144.76,-902.2\"/>\n<text text-anchor=\"middle\" x=\"146.5\" y=\"-939.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x64x56x56</text>\n</g>\n<!-- Layer 11: TIDL_ConvolutionLayer &quot;145&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=176.758896 biasScale=88.498749\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[9] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[11] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.301372,3.682195)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=21.726173\n -->\n<g id=\"node11\" class=\"node\">\n<title>Layer 11: TIDL_ConvolutionLayer &quot;145&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=176.758896 biasScale=88.498749\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [9] \n   Outputs:\n      [11] numDim=0 dims=[1,128,28,28]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-2.301372,3.682195)\n         tensorScale=21.726173\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M99.17,-875C99.17,-875 11.83,-875 11.83,-875 8.67,-875 5.5,-871.83 5.5,-868.67 5.5,-868.67 5.5,-862.33 5.5,-862.33 5.5,-859.17 8.67,-856 11.83,-856 11.83,-856 99.17,-856 99.17,-856 102.33,-856 105.5,-859.17 105.5,-862.33 105.5,-862.33 105.5,-868.67 105.5,-868.67 105.5,-871.83 102.33,-875 99.17,-875\"/>\n<text text-anchor=\"middle\" x=\"55.5\" y=\"-863\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [10 11]</text>\n</g>\n<!-- Layer 9: TIDL_ConvolutionLayer &quot;143&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=601.798462 biasScale=172.955078\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[8] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[9] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.288182)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=62.932056\n&#45;&gt;Layer 11: TIDL_ConvolutionLayer &quot;145&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=176.758896 biasScale=88.498749\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[9] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[11] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.301372,3.682195)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=21.726173\n -->\n<g id=\"edge12\" class=\"edge\">\n<title>Layer 9: TIDL_ConvolutionLayer &quot;143&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=601.798462 biasScale=172.955078\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [8] \n   Outputs:\n      [9] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.288182)\n         tensorScale=62.932056\n-&gt;Layer 11: TIDL_ConvolutionLayer &quot;145&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=176.758896 biasScale=88.498749\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [9] \n   Outputs:\n      [11] numDim=0 dims=[1,128,28,28]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-2.301372,3.682195)\n         tensorScale=21.726173\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M50.91,-909.77C48.71,-907.5 46.72,-904.88 45.5,-902 42.21,-894.22 43.23,-891.13 45.5,-883 45.78,-881.98 46.15,-880.97 46.57,-879.97\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"49.05,-875.17 48.76,-880.64 47.9,-877.39 46.76,-879.61 46.76,-879.61 46.76,-879.61 47.9,-877.39 44.76,-878.58 49.05,-875.17 49.05,-875.17\"/>\n<text text-anchor=\"middle\" x=\"67.5\" y=\"-890.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x128x28x28</text>\n</g>\n<!-- Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[11] [10] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[12] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=43.452347\n -->\n<g id=\"node13\" class=\"node\">\n<title>Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [11] [10] \n   Outputs:\n      [12] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n         tensorScale=43.452347\n</title>\n<path fill=\"#209070\" stroke=\"#000000\" d=\"M138.17,-831C138.17,-831 70.83,-831 70.83,-831 67.67,-831 64.5,-827.83 64.5,-824.67 64.5,-824.67 64.5,-818.33 64.5,-818.33 64.5,-815.17 67.67,-812 70.83,-812 70.83,-812 138.17,-812 138.17,-812 141.33,-812 144.5,-815.17 144.5,-818.33 144.5,-818.33 144.5,-824.67 144.5,-824.67 144.5,-827.83 141.33,-831 138.17,-831\"/>\n<text text-anchor=\"middle\" x=\"104.5\" y=\"-819\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">EltWise [12 12]</text>\n</g>\n<!-- Layer 11: TIDL_ConvolutionLayer &quot;145&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=176.758896 biasScale=88.498749\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[9] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[11] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.301372,3.682195)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=21.726173\n&#45;&gt;Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[11] [10] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[12] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=43.452347\n -->\n<g id=\"edge14\" class=\"edge\">\n<title>Layer 11: TIDL_ConvolutionLayer &quot;145&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=176.758896 biasScale=88.498749\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [9] \n   Outputs:\n      [11] numDim=0 dims=[1,128,28,28]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-2.301372,3.682195)\n         tensorScale=21.726173\n-&gt;Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [11] [10] \n   Outputs:\n      [12] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n         tensorScale=43.452347\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M65.89,-855.59C73,-849.5 82.52,-841.34 90.32,-834.65\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"94.46,-831.11 92.13,-836.07 92.56,-832.73 90.66,-834.36 90.66,-834.36 90.66,-834.36 92.56,-832.73 89.2,-832.65 94.46,-831.11 94.46,-831.11\"/>\n<text text-anchor=\"middle\" x=\"106.5\" y=\"-841.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x128x28x28</text>\n</g>\n<!-- Layer 10: TIDL_ConvolutionLayer &quot;147&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n &#160;&#160;weightScale=184.904083 biasScale=115.278854\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[8] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[10] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=7\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.042818,1.654941)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=38.672062\n&#45;&gt;Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[11] [10] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[12] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=43.452347\n -->\n<g id=\"edge15\" class=\"edge\">\n<title>Layer 10: TIDL_ConvolutionLayer &quot;147&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=64 numOutChannels=128 numGroups=1\n   kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n   weightScale=184.904083 biasScale=115.278854\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [8] \n   Outputs:\n      [10] numDim=0 dims=[1,128,28,28]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=7\n         min/maxValue=(0,0) min/maxTensorValue=(-2.042818,1.654941)\n         tensorScale=38.672062\n-&gt;Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [11] [10] \n   Outputs:\n      [12] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n         tensorScale=43.452347\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M147.34,-882.84C145.47,-871.69 140.88,-852.16 130.5,-839 129.16,-837.3 127.59,-835.72 125.9,-834.28\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"121.79,-831.13 127.13,-832.38 123.78,-832.65 125.76,-834.17 125.76,-834.17 125.76,-834.17 123.78,-832.65 124.4,-835.96 121.79,-831.13 121.79,-831.13\"/>\n<text text-anchor=\"middle\" x=\"168.5\" y=\"-863.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x128x28x28</text>\n</g>\n<!-- Layer 13: TIDL_ConvolutionLayer &quot;152&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=411.508575 biasScale=155.012558\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[12] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[13] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.932776)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=69.847710\n -->\n<g id=\"node14\" class=\"node\">\n<title>Layer 13: TIDL_ConvolutionLayer &quot;152&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=411.508575 biasScale=155.012558\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [12] \n   Outputs:\n      [13] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.932776)\n         tensorScale=69.847710\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M99.67,-787C99.67,-787 11.33,-787 11.33,-787 8.17,-787 5,-783.83 5,-780.67 5,-780.67 5,-774.33 5,-774.33 5,-771.17 8.17,-768 11.33,-768 11.33,-768 99.67,-768 99.67,-768 102.83,-768 106,-771.17 106,-774.33 106,-774.33 106,-780.67 106,-780.67 106,-783.83 102.83,-787 99.67,-787\"/>\n<text text-anchor=\"middle\" x=\"55.5\" y=\"-775\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [13 13]</text>\n</g>\n<!-- Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[11] [10] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[12] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=43.452347\n&#45;&gt;Layer 13: TIDL_ConvolutionLayer &quot;152&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=411.508575 biasScale=155.012558\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[12] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[13] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.932776)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=69.847710\n -->\n<g id=\"edge16\" class=\"edge\">\n<title>Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [11] [10] \n   Outputs:\n      [12] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n         tensorScale=43.452347\n-&gt;Layer 13: TIDL_ConvolutionLayer &quot;152&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=411.508575 biasScale=155.012558\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [12] \n   Outputs:\n      [13] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.932776)\n         tensorScale=69.847710\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M87.86,-811.99C83.95,-809.64 79.93,-806.93 76.5,-804 72.18,-800.31 68.07,-795.66 64.64,-791.35\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"61.46,-787.19 66.28,-789.79 62.98,-789.18 64.5,-791.16 64.5,-791.16 64.5,-791.16 62.98,-789.18 62.71,-792.53 61.46,-787.19 61.46,-787.19\"/>\n<text text-anchor=\"middle\" x=\"98.5\" y=\"-797.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x128x28x28</text>\n</g>\n<!-- Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[14] [12] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[15] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=39.818394\n -->\n<g id=\"node16\" class=\"node\">\n<title>Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [14] [12] \n   Outputs:\n      [15] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n         tensorScale=39.818394\n</title>\n<path fill=\"#209070\" stroke=\"#000000\" d=\"M133.17,-699C133.17,-699 65.83,-699 65.83,-699 62.67,-699 59.5,-695.83 59.5,-692.67 59.5,-692.67 59.5,-686.33 59.5,-686.33 59.5,-683.17 62.67,-680 65.83,-680 65.83,-680 133.17,-680 133.17,-680 136.33,-680 139.5,-683.17 139.5,-686.33 139.5,-686.33 139.5,-692.67 139.5,-692.67 139.5,-695.83 136.33,-699 133.17,-699\"/>\n<text text-anchor=\"middle\" x=\"99.5\" y=\"-687\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">EltWise [15 15]</text>\n</g>\n<!-- Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[11] [10] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[12] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=43.452347\n&#45;&gt;Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[14] [12] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[15] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=39.818394\n -->\n<g id=\"edge19\" class=\"edge\">\n<title>Layer 12: TIDL_EltWiseLayer &quot;149&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [11] [10] \n   Outputs:\n      [12] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.682195)\n         tensorScale=43.452347\n-&gt;Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [14] [12] \n   Outputs:\n      [15] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n         tensorScale=39.818394\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M115.42,-811.67C117.49,-809.41 119.36,-806.81 120.5,-804 136.69,-764.04 139.35,-745.77 120.5,-707 119.77,-705.5 118.83,-704.09 117.75,-702.79\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"114.19,-699.17 119.3,-701.15 115.94,-700.95 117.7,-702.73 117.7,-702.73 117.7,-702.73 115.94,-700.95 116.09,-704.31 114.19,-699.17 114.19,-699.17\"/>\n<text text-anchor=\"middle\" x=\"156.5\" y=\"-753.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x128x28x28</text>\n</g>\n<!-- Layer 14: TIDL_ConvolutionLayer &quot;154&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=145.939056 biasScale=110.417320\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[13] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[14] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;3.013683,2.687200)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=39.818394\n -->\n<g id=\"node15\" class=\"node\">\n<title>Layer 14: TIDL_ConvolutionLayer &quot;154&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=145.939056 biasScale=110.417320\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [13] \n   Outputs:\n      [14] numDim=0 dims=[1,128,28,28]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-3.013683,2.687200)\n         tensorScale=39.818394\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M99.67,-743C99.67,-743 11.33,-743 11.33,-743 8.17,-743 5,-739.83 5,-736.67 5,-736.67 5,-730.33 5,-730.33 5,-727.17 8.17,-724 11.33,-724 11.33,-724 99.67,-724 99.67,-724 102.83,-724 106,-727.17 106,-730.33 106,-730.33 106,-736.67 106,-736.67 106,-739.83 102.83,-743 99.67,-743\"/>\n<text text-anchor=\"middle\" x=\"55.5\" y=\"-731\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [14 14]</text>\n</g>\n<!-- Layer 13: TIDL_ConvolutionLayer &quot;152&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=411.508575 biasScale=155.012558\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[12] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[13] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.932776)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=69.847710\n&#45;&gt;Layer 14: TIDL_ConvolutionLayer &quot;154&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=145.939056 biasScale=110.417320\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[13] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[14] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;3.013683,2.687200)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=39.818394\n -->\n<g id=\"edge17\" class=\"edge\">\n<title>Layer 13: TIDL_ConvolutionLayer &quot;152&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=411.508575 biasScale=155.012558\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [12] \n   Outputs:\n      [13] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.932776)\n         tensorScale=69.847710\n-&gt;Layer 14: TIDL_ConvolutionLayer &quot;154&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=145.939056 biasScale=110.417320\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [13] \n   Outputs:\n      [14] numDim=0 dims=[1,128,28,28]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-3.013683,2.687200)\n         tensorScale=39.818394\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M55.5,-767.59C55.5,-761.95 55.5,-754.54 55.5,-748.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"55.5,-743.11 57.75,-748.11 55.5,-745.61 55.5,-748.11 55.5,-748.11 55.5,-748.11 55.5,-745.61 53.25,-748.11 55.5,-743.11 55.5,-743.11\"/>\n<text text-anchor=\"middle\" x=\"77.5\" y=\"-753.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x128x28x28</text>\n</g>\n<!-- Layer 14: TIDL_ConvolutionLayer &quot;154&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=145.939056 biasScale=110.417320\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[13] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[14] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;3.013683,2.687200)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=39.818394\n&#45;&gt;Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[14] [12] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[15] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=39.818394\n -->\n<g id=\"edge18\" class=\"edge\">\n<title>Layer 14: TIDL_ConvolutionLayer &quot;154&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=128 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=145.939056 biasScale=110.417320\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [13] \n   Outputs:\n      [14] numDim=0 dims=[1,128,28,28]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-3.013683,2.687200)\n         tensorScale=39.818394\n-&gt;Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [14] [12] \n   Outputs:\n      [15] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n         tensorScale=39.818394\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M61.62,-723.99C65.56,-718.79 70.97,-712.17 76.5,-707 78.29,-705.33 80.26,-703.68 82.26,-702.11\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"86.39,-699.02 83.73,-703.82 84.39,-700.52 82.38,-702.02 82.38,-702.02 82.38,-702.02 84.39,-700.52 81.04,-700.21 86.39,-699.02 86.39,-699.02\"/>\n<text text-anchor=\"middle\" x=\"98.5\" y=\"-709.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x128x28x28</text>\n</g>\n<!-- Layer 16: TIDL_ConvolutionLayer &quot;159&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=543.023193 biasScale=148.614471\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[15] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[16] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.557359)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=84.462151\n -->\n<g id=\"node17\" class=\"node\">\n<title>Layer 16: TIDL_ConvolutionLayer &quot;159&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=543.023193 biasScale=148.614471\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [15] \n   Outputs:\n      [16] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.557359)\n         tensorScale=84.462151\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M98.67,-655C98.67,-655 10.33,-655 10.33,-655 7.17,-655 4,-651.83 4,-648.67 4,-648.67 4,-642.33 4,-642.33 4,-639.17 7.17,-636 10.33,-636 10.33,-636 98.67,-636 98.67,-636 101.83,-636 105,-639.17 105,-642.33 105,-642.33 105,-648.67 105,-648.67 105,-651.83 101.83,-655 98.67,-655\"/>\n<text text-anchor=\"middle\" x=\"54.5\" y=\"-643\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [16 16]</text>\n</g>\n<!-- Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[14] [12] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[15] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=39.818394\n&#45;&gt;Layer 16: TIDL_ConvolutionLayer &quot;159&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=543.023193 biasScale=148.614471\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[15] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[16] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.557359)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=84.462151\n -->\n<g id=\"edge20\" class=\"edge\">\n<title>Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [14] [12] \n   Outputs:\n      [15] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n         tensorScale=39.818394\n-&gt;Layer 16: TIDL_ConvolutionLayer &quot;159&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=543.023193 biasScale=148.614471\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [15] \n   Outputs:\n      [16] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.557359)\n         tensorScale=84.462151\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M83.03,-679.91C79.36,-677.6 75.63,-674.93 72.5,-672 68.66,-668.41 65.15,-663.88 62.27,-659.64\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"59.4,-655.21 64.01,-658.19 60.76,-657.31 62.12,-659.41 62.12,-659.41 62.12,-659.41 60.76,-657.31 60.23,-660.63 59.4,-655.21 59.4,-655.21\"/>\n<text text-anchor=\"middle\" x=\"94.5\" y=\"-665.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x128x28x28</text>\n</g>\n<!-- Layer 17: TIDL_ConvolutionLayer &quot;163&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n &#160;&#160;weightScale=313.601562 biasScale=381.469971\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[15] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[17] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;1.414579,0.881549)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=48.777775\n -->\n<g id=\"node19\" class=\"node\">\n<title>Layer 17: TIDL_ConvolutionLayer &quot;163&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n   kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n   weightScale=313.601562 biasScale=381.469971\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [15] \n   Outputs:\n      [17] numDim=0 dims=[1,256,14,14]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-1.414579,0.881549)\n         tensorScale=48.777775\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M188.67,-628C188.67,-628 100.33,-628 100.33,-628 97.17,-628 94,-624.83 94,-621.67 94,-621.67 94,-615.33 94,-615.33 94,-612.17 97.17,-609 100.33,-609 100.33,-609 188.67,-609 188.67,-609 191.83,-609 195,-612.17 195,-615.33 195,-615.33 195,-621.67 195,-621.67 195,-624.83 191.83,-628 188.67,-628\"/>\n<text text-anchor=\"middle\" x=\"144.5\" y=\"-616\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [18 17]</text>\n</g>\n<!-- Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[14] [12] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[15] numDim=0 dims=[1,128,28,28] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=39.818394\n&#45;&gt;Layer 17: TIDL_ConvolutionLayer &quot;163&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n &#160;&#160;weightScale=313.601562 biasScale=381.469971\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[15] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[17] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;1.414579,0.881549)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=48.777775\n -->\n<g id=\"edge22\" class=\"edge\">\n<title>Layer 15: TIDL_EltWiseLayer &quot;156&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [14] [12] \n   Outputs:\n      [15] numDim=0 dims=[1,128,28,28]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[122880,960,29]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.495410)\n         tensorScale=39.818394\n-&gt;Layer 17: TIDL_ConvolutionLayer &quot;163&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n   kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n   weightScale=313.601562 biasScale=381.469971\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [15] \n   Outputs:\n      [17] numDim=0 dims=[1,256,14,14]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-1.414579,0.881549)\n         tensorScale=48.777775\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M109.4,-679.9C111.88,-677.49 114.42,-674.76 116.5,-672 125.76,-659.69 133.74,-643.9 138.78,-632.87\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"140.89,-628.16 140.9,-633.65 139.86,-630.44 138.84,-632.73 138.84,-632.73 138.84,-632.73 139.86,-630.44 136.79,-631.81 140.89,-628.16 140.89,-628.16\"/>\n<text text-anchor=\"middle\" x=\"144.5\" y=\"-665.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x128x28x28</text>\n</g>\n<!-- Layer 18: TIDL_ConvolutionLayer &quot;161&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=226.982880 biasScale=210.129059\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[16] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[18] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=10\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.029683,4.433256)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=18.722132\n -->\n<g id=\"node18\" class=\"node\">\n<title>Layer 18: TIDL_ConvolutionLayer &quot;161&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=226.982880 biasScale=210.129059\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [16] \n   Outputs:\n      [18] numDim=0 dims=[1,256,14,14]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=10\n         min/maxValue=(0,0) min/maxTensorValue=(-2.029683,4.433256)\n         tensorScale=18.722132\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M94.67,-601C94.67,-601 6.33,-601 6.33,-601 3.17,-601 0,-597.83 0,-594.67 0,-594.67 0,-588.33 0,-588.33 0,-585.17 3.17,-582 6.33,-582 6.33,-582 94.67,-582 94.67,-582 97.83,-582 101,-585.17 101,-588.33 101,-588.33 101,-594.67 101,-594.67 101,-597.83 97.83,-601 94.67,-601\"/>\n<text text-anchor=\"middle\" x=\"50.5\" y=\"-589\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [17 18]</text>\n</g>\n<!-- Layer 16: TIDL_ConvolutionLayer &quot;159&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=543.023193 biasScale=148.614471\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[15] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[16] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.557359)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=84.462151\n&#45;&gt;Layer 18: TIDL_ConvolutionLayer &quot;161&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=226.982880 biasScale=210.129059\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[16] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[18] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=10\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.029683,4.433256)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=18.722132\n -->\n<g id=\"edge21\" class=\"edge\">\n<title>Layer 16: TIDL_ConvolutionLayer &quot;159&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=543.023193 biasScale=148.614471\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [15] \n   Outputs:\n      [16] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.557359)\n         tensorScale=84.462151\n-&gt;Layer 18: TIDL_ConvolutionLayer &quot;161&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=226.982880 biasScale=210.129059\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [16] \n   Outputs:\n      [18] numDim=0 dims=[1,256,14,14]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=10\n         min/maxValue=(0,0) min/maxTensorValue=(-2.029683,4.433256)\n         tensorScale=18.722132\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M45.22,-635.83C43.29,-633.49 41.54,-630.82 40.5,-628 37.59,-620.07 38.23,-617.13 40.5,-609 40.78,-607.98 41.15,-606.97 41.57,-605.97\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"44.05,-601.17 43.76,-606.64 42.9,-603.39 41.76,-605.61 41.76,-605.61 41.76,-605.61 42.9,-603.39 39.76,-604.58 44.05,-601.17 44.05,-601.17\"/>\n<text text-anchor=\"middle\" x=\"62.5\" y=\"-616.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x256x14x14</text>\n</g>\n<!-- Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[18] [17] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[19] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=37.444263\n -->\n<g id=\"node20\" class=\"node\">\n<title>Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [18] [17] \n   Outputs:\n      [19] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n         tensorScale=37.444263\n</title>\n<path fill=\"#209070\" stroke=\"#000000\" d=\"M134.17,-557C134.17,-557 66.83,-557 66.83,-557 63.67,-557 60.5,-553.83 60.5,-550.67 60.5,-550.67 60.5,-544.33 60.5,-544.33 60.5,-541.17 63.67,-538 66.83,-538 66.83,-538 134.17,-538 134.17,-538 137.33,-538 140.5,-541.17 140.5,-544.33 140.5,-544.33 140.5,-550.67 140.5,-550.67 140.5,-553.83 137.33,-557 134.17,-557\"/>\n<text text-anchor=\"middle\" x=\"100.5\" y=\"-545\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">EltWise [19 19]</text>\n</g>\n<!-- Layer 18: TIDL_ConvolutionLayer &quot;161&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=226.982880 biasScale=210.129059\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[16] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[18] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=10\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.029683,4.433256)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=18.722132\n&#45;&gt;Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[18] [17] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[19] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=37.444263\n -->\n<g id=\"edge23\" class=\"edge\">\n<title>Layer 18: TIDL_ConvolutionLayer &quot;161&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=226.982880 biasScale=210.129059\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [16] \n   Outputs:\n      [18] numDim=0 dims=[1,256,14,14]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=10\n         min/maxValue=(0,0) min/maxTensorValue=(-2.029683,4.433256)\n         tensorScale=18.722132\n-&gt;Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [18] [17] \n   Outputs:\n      [19] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n         tensorScale=37.444263\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M61.1,-581.59C68.36,-575.5 78.07,-567.34 86.04,-560.65\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"90.25,-557.11 87.87,-562.05 88.34,-558.72 86.42,-560.32 86.42,-560.32 86.42,-560.32 88.34,-558.72 84.98,-558.6 90.25,-557.11 90.25,-557.11\"/>\n<text text-anchor=\"middle\" x=\"102.5\" y=\"-567.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x256x14x14</text>\n</g>\n<!-- Layer 17: TIDL_ConvolutionLayer &quot;163&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n &#160;&#160;weightScale=313.601562 biasScale=381.469971\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[15] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[17] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;1.414579,0.881549)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=48.777775\n&#45;&gt;Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[18] [17] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[19] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=37.444263\n -->\n<g id=\"edge24\" class=\"edge\">\n<title>Layer 17: TIDL_ConvolutionLayer &quot;163&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=128 numOutChannels=256 numGroups=1\n   kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n   weightScale=313.601562 biasScale=381.469971\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [15] \n   Outputs:\n      [17] numDim=0 dims=[1,256,14,14]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-1.414579,0.881549)\n         tensorScale=48.777775\n-&gt;Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [18] [17] \n   Outputs:\n      [19] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n         tensorScale=37.444263\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M143.34,-608.84C141.47,-597.69 136.88,-578.16 126.5,-565 125.16,-563.3 123.59,-561.72 121.9,-560.28\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"117.79,-557.13 123.13,-558.38 119.78,-558.65 121.76,-560.17 121.76,-560.17 121.76,-560.17 119.78,-558.65 120.4,-561.96 117.79,-557.13 117.79,-557.13\"/>\n<text text-anchor=\"middle\" x=\"164.5\" y=\"-589.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x256x14x14</text>\n</g>\n<!-- Layer 20: TIDL_ConvolutionLayer &quot;168&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=469.926483 biasScale=158.667999\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[19] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[20] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.978626)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=68.734573\n -->\n<g id=\"node21\" class=\"node\">\n<title>Layer 20: TIDL_ConvolutionLayer &quot;168&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=469.926483 biasScale=158.667999\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [19] \n   Outputs:\n      [20] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.978626)\n         tensorScale=68.734573\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M105.67,-513C105.67,-513 17.33,-513 17.33,-513 14.17,-513 11,-509.83 11,-506.67 11,-506.67 11,-500.33 11,-500.33 11,-497.17 14.17,-494 17.33,-494 17.33,-494 105.67,-494 105.67,-494 108.83,-494 112,-497.17 112,-500.33 112,-500.33 112,-506.67 112,-506.67 112,-509.83 108.83,-513 105.67,-513\"/>\n<text text-anchor=\"middle\" x=\"61.5\" y=\"-501\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [20 20]</text>\n</g>\n<!-- Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[18] [17] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[19] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=37.444263\n&#45;&gt;Layer 20: TIDL_ConvolutionLayer &quot;168&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=469.926483 biasScale=158.667999\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[19] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[20] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.978626)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=68.734573\n -->\n<g id=\"edge25\" class=\"edge\">\n<title>Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [18] [17] \n   Outputs:\n      [19] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n         tensorScale=37.444263\n-&gt;Layer 20: TIDL_ConvolutionLayer &quot;168&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=469.926483 biasScale=158.667999\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [19] \n   Outputs:\n      [20] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.978626)\n         tensorScale=68.734573\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M90.36,-537.66C87.73,-535.25 84.95,-532.58 82.5,-530 78.71,-526.01 74.81,-521.42 71.42,-517.25\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"68.21,-513.26 73.1,-515.75 69.78,-515.21 71.34,-517.16 71.34,-517.16 71.34,-517.16 69.78,-515.21 69.58,-518.56 68.21,-513.26 68.21,-513.26\"/>\n<text text-anchor=\"middle\" x=\"104.5\" y=\"-523.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x256x14x14</text>\n</g>\n<!-- Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[21] [19] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[22] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.851547\n -->\n<g id=\"node23\" class=\"node\">\n<title>Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [21] [19] \n   Outputs:\n      [22] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n         tensorScale=70.851547\n</title>\n<path fill=\"#209070\" stroke=\"#000000\" d=\"M139.17,-425C139.17,-425 71.83,-425 71.83,-425 68.67,-425 65.5,-421.83 65.5,-418.67 65.5,-418.67 65.5,-412.33 65.5,-412.33 65.5,-409.17 68.67,-406 71.83,-406 71.83,-406 139.17,-406 139.17,-406 142.33,-406 145.5,-409.17 145.5,-412.33 145.5,-412.33 145.5,-418.67 145.5,-418.67 145.5,-421.83 142.33,-425 139.17,-425\"/>\n<text text-anchor=\"middle\" x=\"105.5\" y=\"-413\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">EltWise [22 22]</text>\n</g>\n<!-- Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[18] [17] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[19] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=37.444263\n&#45;&gt;Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[21] [19] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[22] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.851547\n -->\n<g id=\"edge28\" class=\"edge\">\n<title>Layer 19: TIDL_EltWiseLayer &quot;165&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [18] [17] \n   Outputs:\n      [19] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,4.192899)\n         tensorScale=37.444263\n-&gt;Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [21] [19] \n   Outputs:\n      [22] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n         tensorScale=70.851547\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M119.4,-537.83C122.25,-535.69 124.8,-533.09 126.5,-530 147.27,-492.22 145.35,-471.77 126.5,-433 125.77,-431.5 124.83,-430.09 123.75,-428.79\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"120.19,-425.17 125.3,-427.15 121.94,-426.95 123.7,-428.73 123.7,-428.73 123.7,-428.73 121.94,-426.95 122.09,-430.31 120.19,-425.17 120.19,-425.17\"/>\n<text text-anchor=\"middle\" x=\"163.5\" y=\"-479.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x256x14x14</text>\n</g>\n<!-- Layer 21: TIDL_ConvolutionLayer &quot;170&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=131.942307 biasScale=120.631569\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[20] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[21] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;3.246224,2.540523)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=35.425774\n -->\n<g id=\"node22\" class=\"node\">\n<title>Layer 21: TIDL_ConvolutionLayer &quot;170&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=131.942307 biasScale=120.631569\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [20] \n   Outputs:\n      [21] numDim=0 dims=[1,256,14,14]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-3.246224,2.540523)\n         tensorScale=35.425774\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M105.67,-469C105.67,-469 17.33,-469 17.33,-469 14.17,-469 11,-465.83 11,-462.67 11,-462.67 11,-456.33 11,-456.33 11,-453.17 14.17,-450 17.33,-450 17.33,-450 105.67,-450 105.67,-450 108.83,-450 112,-453.17 112,-456.33 112,-456.33 112,-462.67 112,-462.67 112,-465.83 108.83,-469 105.67,-469\"/>\n<text text-anchor=\"middle\" x=\"61.5\" y=\"-457\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [21 21]</text>\n</g>\n<!-- Layer 20: TIDL_ConvolutionLayer &quot;168&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=469.926483 biasScale=158.667999\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[19] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[20] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.978626)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=68.734573\n&#45;&gt;Layer 21: TIDL_ConvolutionLayer &quot;170&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=131.942307 biasScale=120.631569\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[20] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[21] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;3.246224,2.540523)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=35.425774\n -->\n<g id=\"edge26\" class=\"edge\">\n<title>Layer 20: TIDL_ConvolutionLayer &quot;168&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=469.926483 biasScale=158.667999\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [19] \n   Outputs:\n      [20] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.978626)\n         tensorScale=68.734573\n-&gt;Layer 21: TIDL_ConvolutionLayer &quot;170&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=131.942307 biasScale=120.631569\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [20] \n   Outputs:\n      [21] numDim=0 dims=[1,256,14,14]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-3.246224,2.540523)\n         tensorScale=35.425774\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M61.5,-493.59C61.5,-487.95 61.5,-480.54 61.5,-474.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"61.5,-469.11 63.75,-474.11 61.5,-471.61 61.5,-474.11 61.5,-474.11 61.5,-474.11 61.5,-471.61 59.25,-474.11 61.5,-469.11 61.5,-469.11\"/>\n<text text-anchor=\"middle\" x=\"83.5\" y=\"-479.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x256x14x14</text>\n</g>\n<!-- Layer 21: TIDL_ConvolutionLayer &quot;170&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=131.942307 biasScale=120.631569\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[20] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[21] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;3.246224,2.540523)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=35.425774\n&#45;&gt;Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[21] [19] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[22] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.851547\n -->\n<g id=\"edge27\" class=\"edge\">\n<title>Layer 21: TIDL_ConvolutionLayer &quot;170&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=256 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=131.942307 biasScale=120.631569\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [20] \n   Outputs:\n      [21] numDim=0 dims=[1,256,14,14]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-3.246224,2.540523)\n         tensorScale=35.425774\n-&gt;Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [21] [19] \n   Outputs:\n      [22] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n         tensorScale=70.851547\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M67.62,-449.99C71.56,-444.79 76.97,-438.17 82.5,-433 84.29,-431.33 86.26,-429.68 88.26,-428.11\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"92.39,-425.02 89.73,-429.82 90.39,-426.52 88.38,-428.02 88.38,-428.02 88.38,-428.02 90.39,-426.52 87.04,-426.21 92.39,-425.02 92.39,-425.02\"/>\n<text text-anchor=\"middle\" x=\"104.5\" y=\"-435.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x256x14x14</text>\n</g>\n<!-- Layer 23: TIDL_ConvolutionLayer &quot;175&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=424.371094 biasScale=226.842682\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[22] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[23] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.575131)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=117.450577\n -->\n<g id=\"node24\" class=\"node\">\n<title>Layer 23: TIDL_ConvolutionLayer &quot;175&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=424.371094 biasScale=226.842682\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [22] \n   Outputs:\n      [23] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.575131)\n         tensorScale=117.450577\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M104.67,-381C104.67,-381 16.33,-381 16.33,-381 13.17,-381 10,-377.83 10,-374.67 10,-374.67 10,-368.33 10,-368.33 10,-365.17 13.17,-362 16.33,-362 16.33,-362 104.67,-362 104.67,-362 107.83,-362 111,-365.17 111,-368.33 111,-368.33 111,-374.67 111,-374.67 111,-377.83 107.83,-381 104.67,-381\"/>\n<text text-anchor=\"middle\" x=\"60.5\" y=\"-369\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [23 23]</text>\n</g>\n<!-- Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[21] [19] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[22] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.851547\n&#45;&gt;Layer 23: TIDL_ConvolutionLayer &quot;175&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=424.371094 biasScale=226.842682\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[22] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[23] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.575131)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=117.450577\n -->\n<g id=\"edge29\" class=\"edge\">\n<title>Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [21] [19] \n   Outputs:\n      [22] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n         tensorScale=70.851547\n-&gt;Layer 23: TIDL_ConvolutionLayer &quot;175&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=424.371094 biasScale=226.842682\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [22] \n   Outputs:\n      [23] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.575131)\n         tensorScale=117.450577\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M87.06,-405.83C83.32,-403.59 79.6,-400.97 76.5,-398 72.84,-394.5 69.66,-389.99 67.12,-385.74\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"64.62,-381.29 69.03,-384.55 65.84,-383.47 67.07,-385.65 67.07,-385.65 67.07,-385.65 65.84,-383.47 65.11,-386.75 64.62,-381.29 64.62,-381.29\"/>\n<text text-anchor=\"middle\" x=\"98.5\" y=\"-391.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x256x14x14</text>\n</g>\n<!-- Layer 24: TIDL_ConvolutionLayer &quot;179&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n &#160;&#160;weightScale=128.229782 biasScale=168.431061\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[22] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[24] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.479616,1.944244)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=35.489368\n -->\n<g id=\"node26\" class=\"node\">\n<title>Layer 24: TIDL_ConvolutionLayer &quot;179&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n   kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n   weightScale=128.229782 biasScale=168.431061\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [22] \n   Outputs:\n      [24] numDim=0 dims=[1,512,7,7]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-2.479616,1.944244)\n         tensorScale=35.489368\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M190.67,-354C190.67,-354 102.33,-354 102.33,-354 99.17,-354 96,-350.83 96,-347.67 96,-347.67 96,-341.33 96,-341.33 96,-338.17 99.17,-335 102.33,-335 102.33,-335 190.67,-335 190.67,-335 193.83,-335 197,-338.17 197,-341.33 197,-341.33 197,-347.67 197,-347.67 197,-350.83 193.83,-354 190.67,-354\"/>\n<text text-anchor=\"middle\" x=\"146.5\" y=\"-342\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [25 24]</text>\n</g>\n<!-- Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[21] [19] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[22] numDim=0 dims=[1,256,14,14] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.851547\n&#45;&gt;Layer 24: TIDL_ConvolutionLayer &quot;179&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n &#160;&#160;weightScale=128.229782 biasScale=168.431061\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[22] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[24] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.479616,1.944244)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=35.489368\n -->\n<g id=\"edge31\" class=\"edge\">\n<title>Layer 22: TIDL_EltWiseLayer &quot;172&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [21] [19] \n   Outputs:\n      [22] numDim=0 dims=[1,256,14,14]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[81920,320,15]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,3.020400)\n         tensorScale=70.851547\n-&gt;Layer 24: TIDL_ConvolutionLayer &quot;179&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n   kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n   weightScale=128.229782 biasScale=168.431061\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [22] \n   Outputs:\n      [24] numDim=0 dims=[1,512,7,7]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-2.479616,1.944244)\n         tensorScale=35.489368\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M114.23,-405.8C116.42,-403.39 118.67,-400.69 120.5,-398 129.05,-385.47 136.46,-369.72 141.16,-358.75\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"143.12,-354.08 143.26,-359.56 142.16,-356.39 141.19,-358.69 141.19,-358.69 141.19,-358.69 142.16,-356.39 139.11,-357.82 143.12,-354.08 143.12,-354.08\"/>\n<text text-anchor=\"middle\" x=\"148.5\" y=\"-391.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x256x14x14</text>\n</g>\n<!-- Layer 25: TIDL_ConvolutionLayer &quot;177&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=111.910149 biasScale=113.717941\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[23] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[25] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.317727,2.473541)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=51.343403\n -->\n<g id=\"node25\" class=\"node\">\n<title>Layer 25: TIDL_ConvolutionLayer &quot;177&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=111.910149 biasScale=113.717941\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [23] \n   Outputs:\n      [25] numDim=0 dims=[1,512,7,7]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-2.317727,2.473541)\n         tensorScale=51.343403\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M100.67,-327C100.67,-327 12.33,-327 12.33,-327 9.17,-327 6,-323.83 6,-320.67 6,-320.67 6,-314.33 6,-314.33 6,-311.17 9.17,-308 12.33,-308 12.33,-308 100.67,-308 100.67,-308 103.83,-308 107,-311.17 107,-314.33 107,-314.33 107,-320.67 107,-320.67 107,-323.83 103.83,-327 100.67,-327\"/>\n<text text-anchor=\"middle\" x=\"56.5\" y=\"-315\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [24 25]</text>\n</g>\n<!-- Layer 23: TIDL_ConvolutionLayer &quot;175&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=424.371094 biasScale=226.842682\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[22] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[23] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.575131)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=117.450577\n&#45;&gt;Layer 25: TIDL_ConvolutionLayer &quot;177&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=111.910149 biasScale=113.717941\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[23] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[25] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.317727,2.473541)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=51.343403\n -->\n<g id=\"edge30\" class=\"edge\">\n<title>Layer 23: TIDL_ConvolutionLayer &quot;175&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[2,2] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=424.371094 biasScale=226.842682\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [22] \n   Outputs:\n      [23] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.575131)\n         tensorScale=117.450577\n-&gt;Layer 25: TIDL_ConvolutionLayer &quot;177&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=111.910149 biasScale=113.717941\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [23] \n   Outputs:\n      [25] numDim=0 dims=[1,512,7,7]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-2.317727,2.473541)\n         tensorScale=51.343403\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M53.41,-361.91C51.81,-359.5 50.34,-356.77 49.5,-354 47.05,-345.92 47.82,-343.28 49.5,-335 49.7,-333.99 49.97,-332.97 50.28,-331.96\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"52.12,-327.02 52.49,-332.5 51.25,-329.37 50.38,-331.71 50.38,-331.71 50.38,-331.71 51.25,-329.37 48.27,-330.93 52.12,-327.02 52.12,-327.02\"/>\n<text text-anchor=\"middle\" x=\"68\" y=\"-342.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x512x7x7</text>\n</g>\n<!-- Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[25] [24] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[26] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.978737\n -->\n<g id=\"node27\" class=\"node\">\n<title>Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [25] [24] \n   Outputs:\n      [26] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n         tensorScale=70.978737\n</title>\n<path fill=\"#209070\" stroke=\"#000000\" d=\"M142.17,-283C142.17,-283 74.83,-283 74.83,-283 71.67,-283 68.5,-279.83 68.5,-276.67 68.5,-276.67 68.5,-270.33 68.5,-270.33 68.5,-267.17 71.67,-264 74.83,-264 74.83,-264 142.17,-264 142.17,-264 145.33,-264 148.5,-267.17 148.5,-270.33 148.5,-270.33 148.5,-276.67 148.5,-276.67 148.5,-279.83 145.33,-283 142.17,-283\"/>\n<text text-anchor=\"middle\" x=\"108.5\" y=\"-271\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">EltWise [26 26]</text>\n</g>\n<!-- Layer 25: TIDL_ConvolutionLayer &quot;177&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=111.910149 biasScale=113.717941\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[23] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[25] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.317727,2.473541)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=51.343403\n&#45;&gt;Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[25] [24] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[26] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.978737\n -->\n<g id=\"edge32\" class=\"edge\">\n<title>Layer 25: TIDL_ConvolutionLayer &quot;177&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=111.910149 biasScale=113.717941\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [23] \n   Outputs:\n      [25] numDim=0 dims=[1,512,7,7]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-2.317727,2.473541)\n         tensorScale=51.343403\n-&gt;Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [25] [24] \n   Outputs:\n      [26] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n         tensorScale=70.978737\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M67.27,-307.8C74.94,-301.6 85.34,-293.2 93.78,-286.39\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"97.74,-283.19 95.26,-288.08 95.79,-284.76 93.85,-286.33 93.85,-286.33 93.85,-286.33 95.79,-284.76 92.44,-284.58 97.74,-283.19 97.74,-283.19\"/>\n<text text-anchor=\"middle\" x=\"106\" y=\"-293.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x512x7x7</text>\n</g>\n<!-- Layer 24: TIDL_ConvolutionLayer &quot;179&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n &#160;&#160;weightScale=128.229782 biasScale=168.431061\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[22] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[24] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;2.479616,1.944244)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=35.489368\n&#45;&gt;Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[25] [24] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[26] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.978737\n -->\n<g id=\"edge33\" class=\"edge\">\n<title>Layer 24: TIDL_ConvolutionLayer &quot;179&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=256 numOutChannels=512 numGroups=1\n   kernelH/W=[1,1] strideH/W=[2,2] padH/W=[0,0] dilationH/W=[1,1]\n   weightScale=128.229782 biasScale=168.431061\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [22] \n   Outputs:\n      [24] numDim=0 dims=[1,512,7,7]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(-2.479616,1.944244)\n         tensorScale=35.489368\n-&gt;Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [25] [24] \n   Outputs:\n      [26] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n         tensorScale=70.978737\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M145.01,-334.65C142.82,-323.64 137.93,-304.63 128.5,-291 127.53,-289.59 126.4,-288.24 125.19,-286.96\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"121.37,-283.33 126.54,-285.14 123.18,-285.05 125,-286.77 125,-286.77 125,-286.77 123.18,-285.05 123.45,-288.4 121.37,-283.33 121.37,-283.33\"/>\n<text text-anchor=\"middle\" x=\"162\" y=\"-315.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x512x7x7</text>\n</g>\n<!-- Layer 27: TIDL_ConvolutionLayer &quot;184&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=436.468719 biasScale=150.381943\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[26] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[27] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.280826)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=121.015617\n -->\n<g id=\"node28\" class=\"node\">\n<title>Layer 27: TIDL_ConvolutionLayer &quot;184&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=436.468719 biasScale=150.381943\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [26] \n   Outputs:\n      [27] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.280826)\n         tensorScale=121.015617\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M100.67,-239C100.67,-239 12.33,-239 12.33,-239 9.17,-239 6,-235.83 6,-232.67 6,-232.67 6,-226.33 6,-226.33 6,-223.17 9.17,-220 12.33,-220 12.33,-220 100.67,-220 100.67,-220 103.83,-220 107,-223.17 107,-226.33 107,-226.33 107,-232.67 107,-232.67 107,-235.83 103.83,-239 100.67,-239\"/>\n<text text-anchor=\"middle\" x=\"56.5\" y=\"-227\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [27 27]</text>\n</g>\n<!-- Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[25] [24] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[26] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.978737\n&#45;&gt;Layer 27: TIDL_ConvolutionLayer &quot;184&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=436.468719 biasScale=150.381943\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[26] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[27] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.280826)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=121.015617\n -->\n<g id=\"edge34\" class=\"edge\">\n<title>Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [25] [24] \n   Outputs:\n      [26] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n         tensorScale=70.978737\n-&gt;Layer 27: TIDL_ConvolutionLayer &quot;184&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=436.468719 biasScale=150.381943\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [26] \n   Outputs:\n      [27] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.280826)\n         tensorScale=121.015617\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M95.06,-263.74C91.56,-261.32 87.83,-258.64 84.5,-256 79.35,-251.91 73.95,-247.13 69.28,-242.82\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"65.55,-239.33 70.74,-241.1 67.38,-241.04 69.21,-242.74 69.21,-242.74 69.21,-242.74 67.38,-241.04 67.67,-244.39 65.55,-239.33 65.55,-239.33\"/>\n<text text-anchor=\"middle\" x=\"103\" y=\"-249.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x512x7x7</text>\n</g>\n<!-- Layer 29: TIDL_EltWiseLayer &quot;188&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[28] [26] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[29] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,16.159016)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=8.292584\n -->\n<g id=\"node30\" class=\"node\">\n<title>Layer 29: TIDL_EltWiseLayer &quot;188&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [28] [26] \n   Outputs:\n      [29] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,16.159016)\n         tensorScale=8.292584\n</title>\n<path fill=\"#209070\" stroke=\"#000000\" d=\"M136.17,-151C136.17,-151 68.83,-151 68.83,-151 65.67,-151 62.5,-147.83 62.5,-144.67 62.5,-144.67 62.5,-138.33 62.5,-138.33 62.5,-135.17 65.67,-132 68.83,-132 68.83,-132 136.17,-132 136.17,-132 139.33,-132 142.5,-135.17 142.5,-138.33 142.5,-138.33 142.5,-144.67 142.5,-144.67 142.5,-147.83 139.33,-151 136.17,-151\"/>\n<text text-anchor=\"middle\" x=\"102.5\" y=\"-139\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">EltWise [29 29]</text>\n</g>\n<!-- Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[25] [24] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[26] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=5\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=70.978737\n&#45;&gt;Layer 29: TIDL_EltWiseLayer &quot;188&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[28] [26] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[29] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,16.159016)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=8.292584\n -->\n<g id=\"edge37\" class=\"edge\">\n<title>Layer 26: TIDL_EltWiseLayer &quot;181&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [25] [24] \n   Outputs:\n      [26] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=5\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,2.944544)\n         tensorScale=70.978737\n-&gt;Layer 29: TIDL_EltWiseLayer &quot;188&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [28] [26] \n   Outputs:\n      [29] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,16.159016)\n         tensorScale=8.292584\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M117.13,-263.74C118.92,-261.4 120.54,-258.76 121.5,-256 135.62,-215.27 139.39,-198.23 121.5,-159 120.81,-157.49 119.91,-156.06 118.87,-154.73\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"115.43,-151.02 120.48,-153.16 117.13,-152.85 118.83,-154.69 118.83,-154.69 118.83,-154.69 117.13,-152.85 117.18,-156.22 115.43,-151.02 115.43,-151.02\"/>\n<text text-anchor=\"middle\" x=\"153\" y=\"-205.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x512x7x7</text>\n</g>\n<!-- Layer 28: TIDL_ConvolutionLayer &quot;186&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=35.084755 biasScale=57.527752\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[27] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[28] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;9.044225,15.194298)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=8.292584\n -->\n<g id=\"node29\" class=\"node\">\n<title>Layer 28: TIDL_ConvolutionLayer &quot;186&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=35.084755 biasScale=57.527752\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [27] \n   Outputs:\n      [28] numDim=0 dims=[1,512,7,7]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-9.044225,15.194298)\n         tensorScale=8.292584\n</title>\n<path fill=\"#375588\" stroke=\"#000000\" d=\"M100.67,-195C100.67,-195 12.33,-195 12.33,-195 9.17,-195 6,-191.83 6,-188.67 6,-188.67 6,-182.33 6,-182.33 6,-179.17 9.17,-176 12.33,-176 12.33,-176 100.67,-176 100.67,-176 103.83,-176 107,-179.17 107,-182.33 107,-182.33 107,-188.67 107,-188.67 107,-191.83 103.83,-195 100.67,-195\"/>\n<text text-anchor=\"middle\" x=\"56.5\" y=\"-183\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Convolution [28 28]</text>\n</g>\n<!-- Layer 27: TIDL_ConvolutionLayer &quot;184&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=436.468719 biasScale=150.381943\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[26] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[27] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=8\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.280826)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=121.015617\n&#45;&gt;Layer 28: TIDL_ConvolutionLayer &quot;186&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=35.084755 biasScale=57.527752\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[27] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[28] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;9.044225,15.194298)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=8.292584\n -->\n<g id=\"edge35\" class=\"edge\">\n<title>Layer 27: TIDL_ConvolutionLayer &quot;184&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=436.468719 biasScale=150.381943\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [26] \n   Outputs:\n      [27] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=8\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,1.280826)\n         tensorScale=121.015617\n-&gt;Layer 28: TIDL_ConvolutionLayer &quot;186&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=35.084755 biasScale=57.527752\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [27] \n   Outputs:\n      [28] numDim=0 dims=[1,512,7,7]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-9.044225,15.194298)\n         tensorScale=8.292584\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M56.5,-219.59C56.5,-213.95 56.5,-206.54 56.5,-200.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"56.5,-195.11 58.75,-200.11 56.5,-197.61 56.5,-200.11 56.5,-200.11 56.5,-200.11 56.5,-197.61 54.25,-200.11 56.5,-195.11 56.5,-195.11\"/>\n<text text-anchor=\"middle\" x=\"75\" y=\"-205.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x512x7x7</text>\n</g>\n<!-- Layer 28: TIDL_ConvolutionLayer &quot;186&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n &#160;&#160;kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n &#160;&#160;weightScale=35.084755 biasScale=57.527752\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[27] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[28] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=9\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;9.044225,15.194298)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=8.292584\n&#45;&gt;Layer 29: TIDL_EltWiseLayer &quot;188&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[28] [26] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[29] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,16.159016)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=8.292584\n -->\n<g id=\"edge36\" class=\"edge\">\n<title>Layer 28: TIDL_ConvolutionLayer &quot;186&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   convolutionType=0 numInChannels=512 numOutChannels=512 numGroups=1\n   kernelH/W=[3,3] strideH/W=[1,1] padH/W=[1,1] dilationH/W=[1,1]\n   weightScale=35.084755 biasScale=57.527752\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [27] \n   Outputs:\n      [28] numDim=0 dims=[1,512,7,7]  elementType=TIDL_SignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=9\n         min/maxValue=(0,0) min/maxTensorValue=(-9.044225,15.194298)\n         tensorScale=8.292584\n-&gt;Layer 29: TIDL_EltWiseLayer &quot;188&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [28] [26] \n   Outputs:\n      [29] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,16.159016)\n         tensorScale=8.292584\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M66.26,-175.59C72.93,-169.5 81.86,-161.34 89.19,-154.65\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"93.07,-151.11 90.9,-156.14 91.23,-152.79 89.38,-154.48 89.38,-154.48 89.38,-154.48 91.23,-152.79 87.86,-152.82 93.07,-151.11 93.07,-151.11\"/>\n<text text-anchor=\"middle\" x=\"103\" y=\"-161.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x512x7x7</text>\n</g>\n<!-- Layer 30: TIDL_PoolingLayer &quot;190&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;poolingtype=TIDL_AveragePooling numChannels=0\n &#160;&#160;inDataQ=0 outDataQ=0 useCeil=0\n &#160;&#160;kernelH/W=[0,0] strideH/W=[1,1] padH/W=[0,0]\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[29] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[30] numDim=0 dims=[1,1,1,512] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[512,512,512]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=10\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.396388)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=33.170338\n -->\n<g id=\"node31\" class=\"node\">\n<title>Layer 30: TIDL_PoolingLayer &quot;190&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   poolingtype=TIDL_AveragePooling numChannels=0\n   inDataQ=0 outDataQ=0 useCeil=0\n   kernelH/W=[0,0] strideH/W=[1,1] padH/W=[0,0]\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [29] \n   Outputs:\n      [30] numDim=0 dims=[1,1,1,512]  elementType=TIDL_UnsignedChar\n         padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[512,512,512]\n         dataQ=0 roundBits=10\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.396388)\n         tensorScale=33.170338\n</title>\n<path fill=\"#338533\" stroke=\"#000000\" d=\"M136.17,-107C136.17,-107 68.83,-107 68.83,-107 65.67,-107 62.5,-103.83 62.5,-100.67 62.5,-100.67 62.5,-94.33 62.5,-94.33 62.5,-91.17 65.67,-88 68.83,-88 68.83,-88 136.17,-88 136.17,-88 139.33,-88 142.5,-91.17 142.5,-94.33 142.5,-94.33 142.5,-100.67 142.5,-100.67 142.5,-103.83 139.33,-107 136.17,-107\"/>\n<text text-anchor=\"middle\" x=\"102.5\" y=\"-95\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Pooling [30 30]</text>\n</g>\n<!-- Layer 29: TIDL_EltWiseLayer &quot;188&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n &#160;&#160;outDataQ=0\n &#160;&#160;biasQ=0 bias:0x0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_RelU\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[28] [26] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[29] numDim=0 dims=[1,512,7,7] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=6\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,16.159016)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=8.292584\n&#45;&gt;Layer 30: TIDL_PoolingLayer &quot;190&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;poolingtype=TIDL_AveragePooling numChannels=0\n &#160;&#160;inDataQ=0 outDataQ=0 useCeil=0\n &#160;&#160;kernelH/W=[0,0] strideH/W=[1,1] padH/W=[0,0]\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[29] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[30] numDim=0 dims=[1,1,1,512] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[512,512,512]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=10\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.396388)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=33.170338\n -->\n<g id=\"edge38\" class=\"edge\">\n<title>Layer 29: TIDL_EltWiseLayer &quot;188&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 eltWiseType=TIDL_EltWiseSum numInData=0\n   outDataQ=0\n   biasQ=0 bias:0x0\n   actParams:\n      actType=TIDL_RelU\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [28] [26] \n   Outputs:\n      [29] numDim=0 dims=[1,512,7,7]  elementType=TIDL_UnsignedChar\n         padH/W=[1,1] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[98304,192,8]\n         dataQ=0 roundBits=6\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,16.159016)\n         tensorScale=8.292584\n-&gt;Layer 30: TIDL_PoolingLayer &quot;190&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   poolingtype=TIDL_AveragePooling numChannels=0\n   inDataQ=0 outDataQ=0 useCeil=0\n   kernelH/W=[0,0] strideH/W=[1,1] padH/W=[0,0]\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [29] \n   Outputs:\n      [30] numDim=0 dims=[1,1,1,512]  elementType=TIDL_UnsignedChar\n         padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[512,512,512]\n         dataQ=0 roundBits=10\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.396388)\n         tensorScale=33.170338\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M102.5,-131.59C102.5,-125.95 102.5,-118.54 102.5,-112.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"102.5,-107.11 104.75,-112.11 102.5,-109.61 102.5,-112.11 102.5,-112.11 102.5,-112.11 102.5,-109.61 100.25,-112.11 102.5,-107.11 102.5,-107.11\"/>\n<text text-anchor=\"middle\" x=\"121\" y=\"-117.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x512x7x7</text>\n</g>\n<!-- Layer 31: TIDL_InnerProductLayer &quot;191&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;activationType=0 numInNodes=512 numOutNodes=1000\n &#160;&#160;weightsQ=0 weightScale=178.961670 zeroWeightValue=0\n &#160;&#160;biasScale=2076.245605 biasQ=0 inDataQ=0 outDataQ=0 interDataQ=0\n &#160;&#160;biasB=0\n &#160;&#160;weights:0xd86d00 bias:0xe03d00\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[30] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[31] numDim=0 dims=[1,1,1,1000] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[1000,1000,1000]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=11\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;5.865013,17.940039)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=2.898545\n -->\n<g id=\"node32\" class=\"node\">\n<title>Layer 31: TIDL_InnerProductLayer &quot;191&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   activationType=0 numInNodes=512 numOutNodes=1000\n   weightsQ=0 weightScale=178.961670 zeroWeightValue=0\n   biasScale=2076.245605 biasQ=0 inDataQ=0 outDataQ=0 interDataQ=0\n   biasB=0\n   weights:0xd86d00 bias:0xe03d00\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [30] \n   Outputs:\n      [31] numDim=0 dims=[1,1,1,1000]  elementType=TIDL_SignedChar\n         padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[1000,1000,1000]\n         dataQ=0 roundBits=11\n         min/maxValue=(0,0) min/maxTensorValue=(-5.865013,17.940039)\n         tensorScale=2.898545\n</title>\n<path fill=\"#30c0d0\" stroke=\"#000000\" d=\"M146.67,-63C146.67,-63 58.33,-63 58.33,-63 55.17,-63 52,-59.83 52,-56.67 52,-56.67 52,-50.33 52,-50.33 52,-47.17 55.17,-44 58.33,-44 58.33,-44 146.67,-44 146.67,-44 149.83,-44 153,-47.17 153,-50.33 153,-50.33 153,-56.67 153,-56.67 153,-59.83 149.83,-63 146.67,-63\"/>\n<text text-anchor=\"middle\" x=\"102.5\" y=\"-51\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">InnerProduct [31 31]</text>\n</g>\n<!-- Layer 30: TIDL_PoolingLayer &quot;190&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;poolingtype=TIDL_AveragePooling numChannels=0\n &#160;&#160;inDataQ=0 outDataQ=0 useCeil=0\n &#160;&#160;kernelH/W=[0,0] strideH/W=[1,1] padH/W=[0,0]\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[29] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[30] numDim=0 dims=[1,1,1,512] &#160;elementType=TIDL_UnsignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[512,512,512]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=10\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.396388)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=33.170338\n&#45;&gt;Layer 31: TIDL_InnerProductLayer &quot;191&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;activationType=0 numInNodes=512 numOutNodes=1000\n &#160;&#160;weightsQ=0 weightScale=178.961670 zeroWeightValue=0\n &#160;&#160;biasScale=2076.245605 biasQ=0 inDataQ=0 outDataQ=0 interDataQ=0\n &#160;&#160;biasB=0\n &#160;&#160;weights:0xd86d00 bias:0xe03d00\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[30] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[31] numDim=0 dims=[1,1,1,1000] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[1000,1000,1000]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=11\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;5.865013,17.940039)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=2.898545\n -->\n<g id=\"edge39\" class=\"edge\">\n<title>Layer 30: TIDL_PoolingLayer &quot;190&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   poolingtype=TIDL_AveragePooling numChannels=0\n   inDataQ=0 outDataQ=0 useCeil=0\n   kernelH/W=[0,0] strideH/W=[1,1] padH/W=[0,0]\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [29] \n   Outputs:\n      [30] numDim=0 dims=[1,1,1,512]  elementType=TIDL_UnsignedChar\n         padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[512,512,512]\n         dataQ=0 roundBits=10\n         min/maxValue=(0,0) min/maxTensorValue=(0.000000,5.396388)\n         tensorScale=33.170338\n-&gt;Layer 31: TIDL_InnerProductLayer &quot;191&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   activationType=0 numInNodes=512 numOutNodes=1000\n   weightsQ=0 weightScale=178.961670 zeroWeightValue=0\n   biasScale=2076.245605 biasQ=0 inDataQ=0 outDataQ=0 interDataQ=0\n   biasB=0\n   weights:0xd86d00 bias:0xe03d00\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [30] \n   Outputs:\n      [31] numDim=0 dims=[1,1,1,1000]  elementType=TIDL_SignedChar\n         padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[1000,1000,1000]\n         dataQ=0 roundBits=11\n         min/maxValue=(0,0) min/maxTensorValue=(-5.865013,17.940039)\n         tensorScale=2.898545\n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M102.5,-87.59C102.5,-81.95 102.5,-74.54 102.5,-68.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" 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  Inputs:\n      [31] \n</title>\n<path fill=\"#707070\" stroke=\"#000000\" d=\"M127.17,-19C127.17,-19 77.83,-19 77.83,-19 74.67,-19 71.5,-15.83 71.5,-12.67 71.5,-12.67 71.5,-6.33 71.5,-6.33 71.5,-3.17 74.67,0 77.83,0 77.83,0 127.17,0 127.17,0 130.33,0 133.5,-3.17 133.5,-6.33 133.5,-6.33 133.5,-12.67 133.5,-12.67 133.5,-15.83 130.33,-19 127.17,-19\"/>\n<text text-anchor=\"middle\" x=\"102.5\" y=\"-7\" font-family=\"Times,serif\" font-size=\"10.00\" fill=\"#ffffff\">Data [32 0]</text>\n</g>\n<!-- Layer 31: TIDL_InnerProductLayer &quot;191&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;activationType=0 numInNodes=512 numOutNodes=1000\n &#160;&#160;weightsQ=0 weightScale=178.961670 zeroWeightValue=0\n &#160;&#160;biasScale=2076.245605 biasQ=0 inDataQ=0 outDataQ=0 interDataQ=0\n &#160;&#160;biasB=0\n &#160;&#160;weights:0xd86d00 bias:0xe03d00\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[30] \n &#160;&#160;Outputs:\n &#160;&#160;&#160;&#160;&#160;[31] numDim=0 dims=[1,1,1,1000] &#160;elementType=TIDL_SignedChar\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[1000,1000,1000]\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;dataQ=0 roundBits=11\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;min/maxValue=(0,0) min/maxTensorValue=(&#45;5.865013,17.940039)\n &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;tensorScale=2.898545\n&#45;&gt;Layer 32: TIDL_DataLayer &quot;input.1_original&quot;\n &#160;&#160;weightsElementSizeInBits=8\n &#160;&#160;strideOffsetMethod=TIDL_StrideOffsetTopLeft\n &#160;&#160;numChannels=0 dataQ=0\n &#160;&#160;actParams:\n &#160;&#160;&#160;&#160;&#160;actType=TIDL_NoAct\n &#160;&#160;&#160;&#160;&#160;slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n &#160;&#160;Inputs:\n &#160;&#160;&#160;&#160;&#160;[31] \n -->\n<g id=\"edge40\" class=\"edge\">\n<title>Layer 31: TIDL_InnerProductLayer &quot;191&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   activationType=0 numInNodes=512 numOutNodes=1000\n   weightsQ=0 weightScale=178.961670 zeroWeightValue=0\n   biasScale=2076.245605 biasQ=0 inDataQ=0 outDataQ=0 interDataQ=0\n   biasB=0\n   weights:0xd86d00 bias:0xe03d00\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [30] \n   Outputs:\n      [31] numDim=0 dims=[1,1,1,1000]  elementType=TIDL_SignedChar\n         padH/W=[0,0] batchPadH/W=[0,0] numBatchH/W=[1,1] pitch=[1000,1000,1000]\n         dataQ=0 roundBits=11\n         min/maxValue=(0,0) min/maxTensorValue=(-5.865013,17.940039)\n         tensorScale=2.898545\n-&gt;Layer 32: TIDL_DataLayer &quot;input.1_original&quot;\n   weightsElementSizeInBits=8\n   strideOffsetMethod=TIDL_StrideOffsetTopLeft\n   numChannels=0 dataQ=0\n   actParams:\n      actType=TIDL_NoAct\n      slopeScale=0.000000 clipMin/Max=(0.000000,0.000000)\n   Inputs:\n      [31] \n</title>\n<path fill=\"none\" stroke=\"black\" stroke-width=\"0.7\" d=\"M102.5,-43.59C102.5,-37.95 102.5,-30.54 102.5,-24.16\"/>\n<polygon fill=\"black\" stroke=\"black\" stroke-width=\"0.7\" points=\"102.5,-19.11 104.75,-24.11 102.5,-21.61 102.5,-24.11 102.5,-24.11 102.5,-24.11 102.5,-21.61 100.25,-24.11 102.5,-19.11 102.5,-19.11\"/>\n<text text-anchor=\"middle\" x=\"122.5\" y=\"-29.6\" font-family=\"Times,serif\" font-size=\"8.00\"> 1x1x1x1000</text>\n</g>\n</g>\n</svg>",
            "text/plain": [
              "<IPython.core.display.SVG object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from IPython.display import SVG, display\n",
        "display(SVG(filename=\"/content/resnet18/tidl_net.bin.svg\"))"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "authorship_tag": "ABX9TyPnDCqQrRf7O1K4SE+epBxv",
      "include_colab_link": true,
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}
